Method and apparatus for equalization in clustered channels

ABSTRACT

This invention relates to an equalization apparatus and an equalization method. A plurality of equalizers is applied to the equalization apparatus to eliminate interferences of multiple clusters in a channel. The weights of the equalizers are calculated under minimum mean square error criterion by gains of delay paths of multiple clusters in the whole channel. Therefore, the interference of different clusters in the whole channel can be greatly eliminated.

This application claims priority of No. 098107234 filed in Taiwan R.O.C.on Mar. 6, 2009 under 35 USC 119, the entire content of which is herebyincorporated by reference.

BACKGROUND OF THE INVENTION

1. Field of Invention

The present invention relates in general to an equalization technique,and more particularly to an equalization technique for a channel withmultiple clusters.

2. Related Art

In a wireless communication environment, there is a multi-pathphenomenon due to diffractions and refractions of electromagnetic wavescaused by obstacles. Therefore, when a channel thereof is observed via atime domain perspective, the channel may have a plurality of delaypaths. Moreover, when the channel is observed via a frequencyperspective, the channel may be regarded as a frequency-selectivechannel.

Taking a present code division multiple access (CDMA) system as anexample, to solve the problem of interference from thefrequency-selective channel, a receiver of the CDMA system generallyapplies an equalization technique for equalizing the frequency-selectivechannel. In other words, an equalizer is used for equalizing thefrequency-selective channel to be a frequency-flat channel, so as toreduce the multipath interference in the received signals.

FIG. 1 is a system block diagram of a receiver of a conventional CDMAapplying an equalizer. Referring to FIG. 1, a channel response of areceived signals r[m] estimated by a channel estimation unit 110,namely, a delay time τ of each delay path within the channel and achannel gain ĥ(τ) corresponding to each delay time are estimated, and aplurality of weights w₀, w₁, w₂, . . . , w_(F-1) of an equalizer 130 arecalculated according to the estimated channel gains ĥ(τ), and then theweights w₀, w₁, w₂, . . . , w_(F-1) are output to the equalizer 130.Next, the equalizer 130 sequentially delays the received signals r[m]for a chip duration T_(C).

Then, after respectively multiplying the original received signal r[m]and the delayed received signals r[m−1], r[m−2], r[m−F+1] with theweights w₀, w₁, w₂, . . . , w_(F-1), a sum of above multiplemultiplications is then outputted by the equalizer 130. A correlator 150de-spreads the equalized signal processed by the equalizer 130 accordingto a spreading code c[n] of a client, and then a decision unit 170demodulates a digital signal {circumflex over (b)}.

A window length of the equalizer 130 is represented by F. For a presentequalization technique, a plurality of documents (for example, note [1])refers to that the window length F of the equalizer has to be greaterthan or equal to double of the channel length thereof, so that theequalizer may effectively eliminate the multipath interference to thereceived signals. Therefore, as to the hardware of the receiver, if thewindow length of channel estimation is L, the window length F of theequalizer is then designed to be 2 L.

However, in case of a relatively serious channel delay spread, thelength of an actual transmission channel is greatly increased, as shownin FIG. 2. FIG. 2 is a diagram illustrating a channel power delayprofile. Referring to FIG. 2, horizontal axis thereof represents delaytimes, and vertical axis represents the channel power on itscorresponding delay time. According to FIG. 2, the delay paths withinthe channel is sparsely distributed on time domain, and the delay pathsmay be grouped into several clusters of cluster 1, cluster 2 . . .cluster P. A reason of such channel phenomenon may be that in a hillyterrain (HT), the electromagnetic waves emitted from the transmitter arereceived by the receiver after a long distance reflection, so that thedelay paths of the different clusters are generated. Alternatively inthe case of soft handover (SHO), the receiver may be just located withintransmission ranges of multiple base stations, so that the receiver maysimultaneously receive signals from the multiple base stations, andtherefore the delay paths of the multiple clusters are generated.

Due to a limitation of the hardware, if the window length of theequalizer of the receiver maintains to be F=2 L, the window length ofthe equalizer may not be enough to cover all the delay paths, so thatthe equalizer cannot effectively equalize the transmission channel, andaccordingly performance of the receiver is degraded.

A U.S patent publication No. 2006/0109892 A1 provides a receiver havingtwo equalizers, as shown in FIG. 3. The two equalizers 335 and 340 ofthe receiver 300 equalize the received signals respectively based ondelay paths 305A and 305B of two clusters. Next, the signals equalizedby the two equalizers 335 and 340 are combined for outputting to a CMIScircuit 352. The CMIS circuit 352 regenerates the signal and feeds backthe regenerated signal to adders 325 and 330 for multipath interferencecancellation.

When the weights are calculated, calculation of a weight of theequalizer 335 only considers a channel response of the delay path 305Afrom the first cluster, and calculation of a weight of the equalizer 340only considers a channel response of the delay path 305B from the secondcluster. In other words, the weights of the equalizers 335 and 340 arenot calculated under a minimum mean square error (MMSE) criterion.Actually, when a signal is transmitted within the channel, the signalreceived by the equalizer 335 is interfered by the delay path 305B ofthe second cluster; however, the equalizer 335 only takes into accountthe delay path 305A of the first cluster. Similarly, the signal receivedby the equalizer 340 is interfered by the delay path 305A of the firstcluster; however, the equalizer 340 only takes into account the delaypath 305B of the second cluster. Therefore, though the two equalizers335 and 340 are applied in the aforementioned patent, interferences ofthe delay paths 305A and 305B cannot be simultaneously mitigated. Sincethe equalizers 334 and 340 cannot totally eliminate the interferenceswithin the channel, the signal restored by the CMIS circuit still hasthe interference. However, the restored signal with the interference isstill fed back to the adders 325 and 330, so that an error propagationphenomenon occurs. Moreover, when signal energy received by the receiveris relatively small, such feed-back mechanism may lead to an excessivesmall signal-to-interference plus noise ratio (SINR) of the receiver,and accordingly the performance of the receiver is degraded.

A receiver with multiple equalizers is provided in US Publication No.2003/0133424 A1 as shown in FIG. 4. FIG. 4 is a system block diagramillustrating a receiver published in US Publication No. 2003/0133424 A1.The receiver 400 includes a plurality of equalizers 408A—408C forreceiving the received signals from a plurality of antennas andequalizing the received signal respectively. After that, the equalizedsignals equalized by the equalizers 408A—408C are operated bytime-alignment and dispreading, the combiner 311 combines thedispreading signals to recover the original signal.

When the weights of the equalizer 408A˜408C are calculated, thecalculation of the weights utilizes a method of direct matrix inversionunder a minimum mean square error (MMSE) criterion. Actually, due to thecalculation of direct matrix inversion, the arithmetic complexity of thereceiver 400 is greatly increased. Also, considering the implementationof hardware, the hardware complexity of the receiver 400 should belimited so that the window length of the equalizers 408A—408C must belimited. Therefore, the equalizers 408A—408C may not be able toeliminate the interference of the received signals while the receivedsignals are transmitted by the longer length of the transmissionchannel.

Note [1]: M. Melvasalo, P. Jänis and V. Koivunen. “Low complexityspace-time MMSE equalization in WCDMA systems,” proc. of 2005 IEEE 16thInternational Symposium on Personal, Indoor and Mobile RadioCommunications, Berlin, Germany, pp. 306-310, 2005.

SUMMARY OF THE INVENTION

It is therefore an objective of the present invention to provide anequalization apparatus and a method thereof, by which a receiver maysufficiently process the received signal, so as to greatly reducemultipath interference from different clusters and increased efficiencyof an equalizer.

To achieve the above-identified or other objectives, the presentinvention provides an equalization apparatus which is used for receivinga received signal, wherein the received signal is transmitted from atransmitter through a transmission channel. The transmission channelincludes a plurality of delay paths, and the delay paths are at leastgrouped into P clusters. The equalization apparatus includes a channelestimation unit, a weight calculation unit, a cluster delay unit, Pequalizers and a combination unit. The channel estimation unit is usedfor estimating gains of the delay paths respectively corresponding tothe P clusters. The weight calculation unit is used for performing aminimum mean square error (MMSE) algorithm to the gains of the delaypaths respectively corresponding to the P clusters, so as to obtain aplurality of first weights to the plurality of P^(th) weights. Thecluster delay unit is used for generating a plurality of cluster delayedsignals by correspondingly delaying the received signal for K₁, K₂, K₃,. . . K_(P) unit time, wherein the received signal is represented asr[m], and the cluster delayed signals are respectively represented asr[m−K₁], r[m−K₂], r[m−K₃] . . . , r[m−K_(P)], wherein “m” is representedas a time index.

The first equalizer to the P^(th) equalizer are correspondingly receivesthe cluster delay signals r[m−K₁], r[m−K₂], r[m−K₃] . . . r[m−K_(P)],equalizing the cluster delayed signals to correspondingly obtain a firstequalized signal to a P^(th) equalized signal according to thecorresponding first weights to the corresponding P^(th) weights. Thecombination unit is used for combining the first equalized signals toP^(th) equalized signal, and outputting a equalized signal. “P” is anature number, and “P” is equal to or larger than 3. “K₁”, “K₂”, “K₃” .. . “K_(P)” and “m” are integers.

The present invention additionally provides an equalization method, themethod includes the steps of: receiving a received signal, wherein thereceived signal is transmitted from a transmitter through a transmissionchannel, wherein the transmission channel has a plurality of delay pathsand the delay paths are at least grouped into P clusters; estimatinggains of the delay paths corresponding to the P clusters; performing anminimum mean square error (MMSE) algorithm to the gains of the delaypaths corresponding to the P clusters to obtain a plurality of firstweights to a plurality of P^(h) weights; respectively delaying thereceived signal for K₁, K₂, K₃ . . . K_(P) unit time to obtain aplurality of cluster delay signals, wherein the received signal isrepresented as r[m], where “m” is represented as a time index, whereinthe cluster delay signals are respectively represented as r[m−K₁],r[m−K₂], r[m−K₃] . . . r[m−K_(P)]; equalizing the cluster delay signalsr[m−K₁], r[m−K₂], r[m−K₃] . . . r[m−K_(P)] to obtain a first equalizedsignal to a P^(th) equalized signal according to the corresponding firstweights to the corresponding P^(th) weights; and combining the firstequalized signal to the P^(th) equalized signal and outputting aequalized signal. “P” is a nature number and larger than 3. “K₁”, “K₂”,“K₃” . . . “K_(P)” and “m” are integers.

In the equalization method according to the preferred embodiment of thepresent invention, the method further includes the steps of: searchingthe delay paths in the transmission channel and the delay timecorresponding to the delay paths; and determining a number of theclusters of the delay paths according to the delay time of the delaypaths and determining a window interval according to the interval of theclusters and the initial delay time of the clusters of the delay paths.

In the equalization method according to the preferred embodiment of thepresent invention, the delay time of the i^(th) delay path in thetransmission channel is represented as D_(i). The steps for determiningthe windows interval comprise: the step (a) of setting the initialnumber of i to 1; the step (b) of calculating a difference between D_(i)and D_(i-1); the step (c) of determining the difference between D, andD_(i-1) is larger than a threshold value, wherein when the hypothesis istrue, the step (d) and the step (e) are performed, when the hypothesisis false, the step (d) is skipped and the step (e) is performed; thestep (d) of adding 1 to a cluster number counter represented as CN, andsetting the delay time of the 1^(st) delay path of a CN^(th) cluster toD_(i); the step (e) of determining whether all delay paths are searched,if the hypothesis is false, performing the step (f) and going back tothe step (b), otherwise performing the step (g); the step (f) of adding1 to i; and the step (g) of determining the window interval according tothe delay time of the 1^(st) delay path of the cluster corresponding toeach cluster number counter.

In the present invention, since a plurality of equalizers arerespectively applied for equalizing the received signal in differentdelay paths of different clusters, and meanwhile the weights of theequalizers are calculated by channel gains of the whole cannel under theMMSE criterion, each equalizer can greatly eliminate the interference ofdifferent clusters in whole channel.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will become more fully understood from thedetailed description given hereinbelow and the accompanying drawingswhich are given by way of illustration only, and thus are not limitativeof the present invention.

FIG. 1 is a system block diagram of a receiver of a conventional CDMAapplying an equalizer.

FIG. 2 is a diagram illustrating a channel power delay profile.

FIG. 3 is a system block diagram illustrating a receiver complying withthe U.S patent laid-open publication No. 2006/0109892 A1.

FIG. 4 is a system block diagram illustrating a receiver complying withthe U.S patent laid-open publication No. 2003/0133424 A1.

FIG. 5 is a system block diagram illustrating a receiver of anequalization apparatus according to an embodiment of the presentinvention.

FIG. 6 is a system block diagram illustrating an equalization apparatusaccording to an embodiment of the present invention.

FIG. 7 is a diagram illustrating the arrangement of the channelestimation window (CE window) according to an embodiment of the presentinvention.

FIG. 8 is a flowchart illustrating a method for determining the windowinterval according to an embodiment of the present invention.

FIG. 9 is a system block diagram illustrating equalizers 660_1˜660_Paccording to an embodiment of the present invention.

FIG. 10 is a system block diagram illustrating the weight calculationunit 640 according to an embodiment of the present invention.

FIG. 11 is a system block diagram illustrating a weight calculation unit1100 according to another embodiment of the present invention.

FIG. 12 is a system block diagram illustrating an equalization apparatusaccording to another embodiment of the present invention.

FIG. 13 is a system block diagram illustrating a weight calculation unit1300 according to another embodiment of the present invention.

FIG. 14 is a flowchart illustrating an equalization method according toan embodiment of the present invention.

FIG. 15 is a flowchart illustrating an equalization method according toanother embodiment of the present invention.

FIG. 16 is a flowchart illustrating the sub-step of the step S1506according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

The present invention will be apparent from the following detaileddescription, which proceeds with reference to the accompanying drawings,wherein the same references relate to the same elements.

In order to reduce an interference of a channel with excessive delayspread to a received signal, the present embodiment of the presentinvention provides an equalization apparatus and a method thereof. Forconveniently describing the present embodiment, a transmission channelpower delay profile is shown in FIG. 2.

As shown in FIG. 2, the distribution of a plurality of delay paths intime domain may be grouped into a first cluster to a P^(th) cluster,wherein the channel length of the first cluster is represented as L₁,the channel length of the second cluster is represented as L₂, . . . ,the channel length of the P^(th) cluster is represented as L_(P). Thedelay time of the first delay path within the first cluster isrepresented as K₁, the delay time of the first delay path within thesecond cluster is represented as K₂, . . . , the delay time of the firstdelay path within the P^(th) cluster is represented as K_(P).

In the following content, the discrete time is used for representing thereceived signal and a channel response. Moreover, according to FIG. 2,the received signal of a m^(th) unit time may be represented by:

$\begin{matrix}{{r\lbrack m\rbrack} = {{\sum\limits_{p = 1}^{P}{\sum\limits_{l = 0}^{L_{p} - 1}{{h\left\lbrack {K_{p} + l} \right\rbrack}{d\left\lbrack {m - K_{p} - l} \right\rbrack}}}} + {v\lbrack m\rbrack}}} & (1)\end{matrix}$

wherein h[•] represents a channel gain, d[•] represents a transmittedsignal from the transmitter, v[•] represents a Gaussian noise, L_(p)represents the number of delay paths within the p^(th) cluster, K_(p)represents the delay time of the first delay path within the p^(th)cluster.

For conveniently describing the present embodiment, it is assumed thatthe equalization apparatus provided by the present embodiment is appliedto a receiver as shown in FIG. 5. FIG. 5 is a system block diagramillustrating a receiver of an equalization apparatus according to anembodiment of the present invention.

Referring to FIG. 5, the receiver 500 includes an equalization apparatus505 and a de-modulation unit 560. The equalization apparatus 505receives a received signal r[m] from a transmitter through atransmission channel and equalizes the received signal r[m] to output aequalized signal q[m] to the de-modulation unit 560. The de-modulationunit 560 demodulates the equalized signal q[m] to obtain a digitalsignal b.

The equalization apparatus 505 provided by the present embodimentincludes a channel estimation unit 510, a weight calculation unit 520, acluster delay unit 530, P equalizers 540_1˜540_P and a combination unit550. The channel estimation unit 510 receives the received signal r[m]and estimates gains of the delay paths respectively corresponding to theP clusters. The weight calculation unit 520 is used for performing aminimum mean square error (MMSE) algorithm to the gains of the delaypaths respectively corresponding to the P clusters, so as to obtain aplurality of weights. And the weight calculation unit 520correspondingly outputs the first weights to the P^(th) weights to theequalizers 540_1˜540_P. The cluster delay unit 530 is used foroutputting a plurality of cluster delayed signals by correspondinglydelaying the received signal for K₁, K₂, K₃, . . . K_(P) unit time,wherein the cluster delayed signals are respectively represented asr[m−K₁], r[m−K₂], r[m−K₃] . . . , r[m−K_(P)]. The equalizers 540_1˜540_Pcorrespondingly receive the cluster delayed signals r[m−K₁], r[m−K₂],r[m−K₃] . . . , r[m−K_(P)] and equalize the cluster delayed signals toobtain a first to a P^(th) equalized signals according to the firstweights to the P^(th) weights and then output the first to the P^(th)equalized signals to the combination unit 550. The combination unit 550combines the first to the P^(th) equalized signals to output theequalized signal q[m].

The time parameters K₁, K₂, K₃, . . . , K_(P) of the cluster delay unit530 can be determined according to the channel estimates obtained by thechannel estimation unit 510. In other words, the channel estimation unit510 estimates the delay time K₁, K₂, K₃, . . . , K_(P) of the firstdelay paths within the first cluster to P^(th) cluster, and then thecluster delay unit 530 determines the time parameters K₁, K₂, K₃, . . ., K_(P) according to the estimated delay time. In addition, a presentMulti-Path Searcher (MPS) can be implemented to search the delay time ofeach cluster, and the cluster delay unit 530 determines the timeparameters K₁, K₂, K₃, . . . , K_(P) according to the searching resultof the MPS.

In order to conveniently explain the present embodiment, the lengths ofthe equalizers 540_1˜540_P are all assumed to be F for example, and theweight calculation unit 520 respectively outputs F weights to theequalizers 540_1˜540_P.

In addition, the p^(th) weights are represented as w _(p)=[w_(p,0)w_(p,1) . . . w_(p,F-1)]^(T), wherein “p” is a nature number between 1to P. In other words, the outputted weights of the weight calculationunit 520 are represented as {w ₁, w ₂, . . . , w _(P)}, wherein eachunder-line in the abovementioned mathematic symbols represents a vector.

The equalization apparatus 505 provided by the present embodiment isused for eliminating the interference of the transmission channel to thereceived signal.

Therefore, under the MMSE criterion, the mean square error between thetransmitted signal and the equalized signal q[m] obtained based on theweights {w ₁, w ₂, . . . , w _(P)} calculated by the weight calculationunit 520 has to be minimized. Namely, under the MMSE criterion, theweights {w ₁, w ₂, . . . , w _(P)} should satisfy the followingequation:

$\begin{matrix}{\left\{ {{\underset{\_}{w}}_{1},{\underset{\_}{w}}_{2},\ldots \mspace{14mu},{\underset{\_}{w}}_{P}} \right\} = {\arg\limits_{\{{{\underset{\_}{w}}_{1},{\underset{\_}{w}}_{2},\ldots \mspace{14mu},{\underset{\_}{w}}_{P}}\}}\min \; E\left\{ {{d\left\lbrack {m - D} \right\rbrack} - {\sum\limits_{p = 1}^{P}{{\underset{\_}{w}}_{p}^{H}{\underset{\_}{r}}_{m - K_{p}}}}} \right\}}} & (2)\end{matrix}$

wherein E[•] in the equation (2) represents an expected value operation,arg min represents that a minimum value of the function is extracted.The superscript H represents a Hermitian operator, D represents adecision delay, r _(m-K) _(p) represents a vector composed by receivedsignals delayed K_(p) unit time, the value thereof is represented as r_(m-K) _(p) =(r[m−K_(p)] r[m−K_(p)−1] . . . r[m−K_(p)−F+1])^(T).

According to the abovementioned equation (2), the weights {w ₁, w ₂, . .. , w _(P)} can be obtained by an adaptive approach or a direct matrixinversion.

The time parameters K₁, K₂, K₃, . . . , K_(P) of the cluster delay unit530 can be determined according to the channel estimates obtained by thechannel estimation unit 510. In other words, the channel estimation unit510 estimates the delay time K₁, K₂, K₃, . . . , K_(P) of the firstdelay paths within the first cluster to P^(th) cluster, and then thecluster delay unit 530 determines the time parameters K₁, K₂, K₃, . . ., K_(P) according to the estimated delay time. In addition, a presentMulti-Path Searcher (MPS) can be implemented to search the delay time ofeach cluster in the present embodiment, and the cluster delay unit 530determines the time parameters K₁, K₂, K₃, . . . , K_(P) according tothe searching result of the MPS.

In the abovementioned embodiment, the equalization apparatus 505utilizes the cluster delay unit 530 to delay the received signal withK₁, K₂, K₃, . . . , K_(P) unit time and then outputs to the equalizers540_1˜540_P. Therefore, the equalizers 540_1˜540_P of the equalizationapparatus 505 are used for eliminating the interference from theclusters in the channel. Meanwhile, the cluster delay unit 530 can beproperly adjusted so that the equalization apparatus 505 can be used toequalize a multipath channel composed by a single cluster with longerchannel length.

Since the weight calculation unit 520 uses the direct matrix inversionor the adaptive approach in progress of calculation of weights, thereceiver 500 has to spend enormous amount of calculation or longerconvergence time. In order to reduce the amount of calculation orconvergence time for calculating the weights, another equalizationapparatus of another embodiment is provided hereinafter as shown in FIG.6. FIG. 6 is a system block diagram illustrating an equalizationapparatus according to an embodiment of the present invention. Referringto FIG. 6, the equalization apparatus 600 includes a multi-path searcher610, a delay parameter generating unit 620, a channel estimation unit630, a weight calculation unit 640, a cluster delay unit 650, equalizers660_1˜660_P and a combination unit 670.

The multi-path searcher 610 scans the transmission channel to obtain thedelay paths and the delay time corresponding to the delay paths. Thesearching result of the multi-path searcher 610 is shown in FIG. 2 as anexample. Afterward, the delay parameter generating unit 620 determinesthe cluster number of the delay paths according to the delay time of thedelay paths and determines a window interval according to the intervalsof the clusters and the initial delay time of the clusters, wherein thewindow interval is represented as K, and the cluster number of the delaypaths is represented as P.

In the present embodiment, in order to reduce the amount of calculationof the equalization apparatus 600, the cluster delay unit 650 utilizesthe window interval K to delay the received signal r[m] for K unit timeso as to obtain a plurality of cluster delay signals r[m], r[m−K],r[m−2K], . . . , r[m−(P−1)K]. And the cluster delay unit 650respectively outputs the cluster delay signals to the first equalizer tothe P^(th) equalizer. In addition, in cooperation with the cluster delayunit 650 and in order to acquire adapted received signals forcalculating the weight of equalizer, the channel estimation unit 630allocates the channel estimation window (hereinafter referred to as CEwindow) as shown in FIG. 7. FIG. 7 is a diagram illustrating thearrangement of the channel estimation window according to an embodimentof the present invention.

Referring to FIG. 7, since the multi-path searcher 610 had alreadysearched P clusters in the present channel, it is assumed that thechannel estimation unit 630 allocates P CE windows to estimate completechannel response, wherein the length of the CE window in the channelestimation unit 630 is represented as W. The first CE window is locatedat the time point when the first delay path arrives to the receiver, andthe delay time is zero. Afterward, the second CE window is disposed at Kunit time from the first CE window, and so on. The interval between eachtwo adjacent CE windows is K unit time. The channel estimation unit 630utilizes P CE window to estimates P segment of channel responses. Owingto the channel estimation is prior art for a person skilled in the art,the present invention does not describe the structure of the channelestimation unit 630 in detail.

From the abovementioned operation of the channel estimation unit 630 andcluster delay unit 650, the window interval K determined by the delayparameter generating unit 620 will affect the quality of the channelestimation unit 630 and the equalizers 660_1˜660_P. FIG. 8 is aflowchart illustrating a method for determining the window intervalaccording to an embodiment of the present invention.

Referring to FIG. 8, the method includes the following steps.

In step S805, the method for determination of window interval starts.

In step S810, the delay parameter generating unit 620 receives thesearching result of the multi-path searcher and collects the delay timeof each delay path from the channel, wherein the delay time of i^(th)delay path is represented as D_(i). These path delays are sorted inascending order. The initial value of i is 0, that is to say, the delaytime of the first delay path is represented as D₀.

In steps S820, the difference between the delay time of the i^(th) delaypath and the (i−1)^(th) delay path is calculated, that is, thedifference between D_(i) and D_(i-1) is calculated.

In step S830, a hypothesis is tested whether the difference between D,and D_(i-1) is larger than a threshold, wherein the threshold value canbe designed according to practical requirement of system.

In step S840, a cluster number counter adds one (hereinafter referred toas CN) when the difference between D_(i) and D_(i-1) is larger than thethreshold value, and the delay time of the first delay path of CN^(th)cluster is set to D_(i), wherein the CN is represented as j, the delaytime of the first delay path of the j^(th) cluster is represented asK_(j). K_(j)=D_(i) is set in the step S840. In addition, the initialvalue of the CN is 1, and the delay time of the first delay path is 0,that is to say, K₁=0. For example, in the FIG. 7, it is observed thatthe delay time of the 7^(th) and the 8^(th) delay path is distantlylong, and, the difference between D₇ and D₆ may be larger than thethreshold value.

Therefore, when i is equal to 7, the determination of the step S830 ispositive so that K₂=D₇ is set in the step S840. In addition, thehypothesis of the step S830 is false, the step S850 is directlyperformed.

In step S850, it is determined whether each delay path is checked.

In step S860, i plus 1 is performed.

In step S870, when each delay path is checked, a window interval K isdetermined according to K₁˜K₃. In addition, in the abovementioned stepS870, the equalizer length, CE window length or total power of delaypaths of each cluster, and so on, can be taken into account fordetermining of parameters of the window interval K.

In step S880, the method for determining window interval in theembodiment of the present invention ends.

Referring to FIG. 6, the weight calculation unit 640 utilizes thechannel response estimated by channel estimation unit 630 to calculatethe plurality of weights under MMSE criterion. Further, the first to theP^(th) weights calculated by the weight calculation unit 640 arecorrespondingly outputted to the equalizers 660_1˜660_P.

For conveniently explaining the present embodiment, the number ofweights outputted from the weight calculation unit 640 to each equalizer660_1˜660_P is assumed as F.

For conveniently describing the present embodiment, assuming thestructure of each equalizer 660_1˜660_P is composed by a FIR (FiniteImpulse Response) filter as shown in FIG. 9. FIG. 9 is a system blockdiagram illustrating equalizers 660_1˜660_P according to an embodimentof the present invention. The p^(th) equalizer 660_p includes (F−1) timedelay apparatuses 662_1˜662_(F−1), F multiplication units664_0˜664_(F−1) and a adder 667 as shown in FIG. 9. The time delayapparatuses 662_1˜662_(F−1) receives the cluster delay signalr[m−(p−1)K] and sequentially delays the cluster delay signal r[m−(p−1)K]for a unit time T and then respectively outputs a plurality ofsubsequently-delayed signals r[m−(p−1)K−1], r[m−(p−1)K−2], . . . ,r[m−(p−1)K−(F−1)]. The F multiplication units 664_0˜664_(F−1)respectively multiply the cluster delay signal r[m−(p−1)K] and thesubsequently-delayed signals r[m−(p−1)K−1], r[m−(p−1)K−2], . . . ,r[m−(p−1)K−(F−1)] with conjugations of the corresponding weightsw_(p,0)*, w_(p,1)*, . . . w_(p,F-1)* to obtain a plurality of multipliedsignals w_(p,0)*·r[m−(p−1)K], w_(p,1)*·r[m−(p−1)K−1], . . . ,w_(p,F-1)*·r[m−(p−1)K−(F−1)]. The adder 667 adds the multiplied signalsw_(p,0)*·r[m−(p−1)K], w_(p,1)*·r[m−(p−1)K−1], . . . ,w_(p,F-1)*·r[m−(p−1)K−(F−1)]. Afterward the adder 667 outputs the sum tothe combination unit 670 as the p^(th) equalization signal. Finally, thecombination unit 670 outputs a equalized signal q[m].

In the following content, how the weight calculation unit 640 calculatesthe weights {w ₁, w ₂, . . . w _(P)} is described. According to theabovementioned description corresponding to the FIG. 7, the length ofthe CE windows in the channel estimation unit is W, and the intervalbetween two adjacent CE windows is K unit time. Therefore, the receivedsignal in equation (1) can be represented as follow.

$\begin{matrix}{{r\lbrack m\rbrack} = {{\sum\limits_{p = 1}^{P}{\sum\limits_{l = 0}^{L_{p} - 1}{{h\left\lbrack {K_{p} + l} \right\rbrack}{d\left\lbrack {m - K_{P} - l} \right\rbrack}}}} + {v\lbrack m\rbrack}}} & (3)\end{matrix}$

In order to simplify the mathematical expression, the received signal isrepresented in vector form as r[m]=(r[m] r[m−1] . . . r[m−F+1])^(T). Andthe signal emitted from the transmitter is also represented in vectorform as d[m]=(d[m] d[m−1] . . . d[m−F−W+2])^(T). Further, the channelresponse estimated from the p^(th) CE window of the channel estimationunit 630 is represented as ĥ[pK], ĥ[pK+1], . . . , ĥ[pK+W−1]. Forconveniently describing the present embodiment, the abovementionedchannel response ĥ[pK], ĥ[pK+1], . . . , ĥ[pK+W−1] can be used forcomposing a Toeplitz matrix represented as:

$\begin{matrix}{{\underset{\underset{\_}{\_}}{H}}_{p} = {\begin{pmatrix}{\hat{h}\lbrack{pK}\rbrack} & {\hat{h}\left\lbrack {{pK} + 1} \right\rbrack} & \ldots & {\hat{h}\left\lbrack {{pK} + W - 1} \right\rbrack} & 0 & \ldots & 0 \\0 & {\hat{h}\lbrack{pK}\rbrack} & {\hat{h}\left\lbrack {{pK} + 1} \right\rbrack} & \ddots & {\hat{h}\left\lbrack {{pK} + W - 1} \right\rbrack} & \ddots & \vdots \\\vdots & \ddots & \ddots & \ddots & \ddots & \ddots & 0 \\0 & \ldots & 0 & {\hat{h}\lbrack{pK}\rbrack} & {\hat{h}\left\lbrack {{pK} + 1} \right\rbrack} & \ldots & {\hat{h}\left\lbrack {{pK} + W - 1} \right\rbrack}\end{pmatrix} \in C^{F \times {({F + W - 1})}}}} & \;\end{matrix}$

wherein the mathematical symbol marked with two bottom lines isrepresented a matrix.

According to the abovementioned mathematical expression, theabovementioned equation (3) can be rewritten as:

$\begin{matrix}{{\underset{\_}{r}\lbrack m\rbrack} = {\sum\limits_{p = 0}^{P - 1}{{\underset{\underset{\_}{\_}}{H}}_{p}{{\underset{\_}{d}\left\lbrack {m - {pK}} \right\rbrack}.}}}} & (4)\end{matrix}$

Expanding the equation (4), the signal received by the equalizers540_1˜540_P can be represented in matrix form as

${\underset{\underset{-}{\underset{r}{}}}{\begin{pmatrix}{\underset{\_}{r}\lbrack m\rbrack} \\{\underset{\_}{r}\left\lbrack {m - K} \right\rbrack} \\\vdots \\{\underset{\_}{r}\left\lbrack {m - {\left( {P - 1} \right)K}} \right\rbrack}\end{pmatrix}} = {{\underset{\underset{-}{\underset{-}{\underset{H}{}}}}{\begin{pmatrix}{\underset{\underset{\_}{\_}}{H}}_{0} & {\underset{\underset{\_}{\_}}{H}}_{1} & \ldots & {\underset{\underset{\_}{\_}}{H}}_{P - 1} & 0 & \ldots & 0 \\0 & {\underset{\underset{\_}{\_}}{H}}_{0} & {\underset{\underset{\_}{\_}}{H}}_{1} & \ldots & {\underset{\underset{\_}{\_}}{H}}_{P - 1} & \ddots & \vdots \\\vdots & \ddots & \ddots & \ddots & \ddots & \ddots & 0 \\0 & \ldots & 0 & {\underset{\underset{\_}{\_}}{H}}_{0} & {\underset{\underset{\_}{\_}}{H}}_{1} & \ldots & {\underset{\underset{\_}{\_}}{H}}_{P - 1}\end{pmatrix}\quad}\underset{\underset{-}{\underset{d}{}}}{\begin{pmatrix}{\underset{\_}{d}\lbrack m\rbrack} \\{d\left\lbrack {m - K} \right\rbrack} \\\vdots \\{d\left\lbrack {m - {2\left( {P - 1} \right)K}} \right\rbrack}\end{pmatrix}}} + \underset{\underset{-}{\underset{v}{}}}{\begin{pmatrix}{\underset{\_}{v}\lbrack m\rbrack} \\{\underset{-}{v}\left\lbrack {m - K} \right\rbrack} \\\vdots \\{\underset{-}{v}\left\lbrack {m - {\left( {P - 1} \right)K}} \right\rbrack}\end{pmatrix}}}},$

wherein r is a received vector composed of the received signals r[n],r[m−K], . . . , r[m−(P−1)K], the value thereof is

$\underset{\_}{r} = {\begin{pmatrix}{\underset{\_}{r}\lbrack m\rbrack} \\{\underset{\_}{r}\left\lbrack {m - K} \right\rbrack} \\\vdots \\{\underset{\_}{r}\left\lbrack {m - {\left( {P - 1} \right)K}} \right\rbrack}\end{pmatrix}.}$

Similarly, d and v are vectors respectively composed of multiplevectors, the values thereof respectively represent

$\underset{\_}{d} = {{\begin{pmatrix}{\underset{\_}{d}\lbrack m\rbrack} \\{d\left\lbrack {m - K} \right\rbrack} \\\vdots \\{d\left\lbrack {m - {2\left( {P - 1} \right)K}} \right\rbrack}\end{pmatrix}\mspace{14mu} {and}\mspace{14mu} \underset{\_}{v}} = {\begin{pmatrix}{\underset{\_}{v}\lbrack m\rbrack} \\{\underset{-}{v}\left\lbrack {m - K} \right\rbrack} \\\vdots \\{\underset{-}{v}\left\lbrack {m - {\left( {P - 1} \right)K}} \right\rbrack}\end{pmatrix}.}}$

The symbol H is a matrix composed of matrices H ₀, H ₁, . . . , H_(P-1). The value thereof is represented as

$\underset{\underset{\_}{\_}}{H} = {\begin{pmatrix}{\underset{\underset{\_}{\_}}{H}}_{0} & {\underset{\underset{\_}{\_}}{H}}_{1} & \ldots & {\underset{\underset{\_}{\_}}{H}}_{P - 1} & 0 & \ldots & 0 \\0 & {\underset{\underset{\_}{\_}}{H}}_{0} & {\underset{\underset{\_}{\_}}{H}}_{1} & \ldots & {\underset{\underset{\_}{\_}}{H}}_{P - 1} & \ddots & \vdots \\\vdots & \ddots & \ddots & \ddots & \ddots & \ddots & 0 \\0 & \ldots & 0 & {\underset{\underset{\_}{\_}}{H}}_{0} & {\underset{\underset{\_}{\_}}{H}}_{1} & \ldots & {\underset{\underset{\_}{\_}}{H}}_{P - 1}\end{pmatrix}.}$

The matrix H can be catalogued a Block-Toeplitz matrix.

In the present embodiment, the equalization apparatus 600 is used foreliminating the interference of the transmission channel to the receivedsignal. Therefore, under MMSE criterion, the equalized signal q[m]obtained based on the weights w _(MMSE) from the weight calculation 640has to be quite similar to the transmitted signal of the transmitter. Inother words, under MMSE criterion, the weights calculated from theweight calculation 640 are chosen to satisfy the following equation:

$\begin{matrix}{{\underset{\_}{w}}_{MMSE} = {\arg\limits_{\underset{\_}{w}}\; \min \; E\left\{ {{{\underset{\_}{d}\left\lbrack {m - D} \right\rbrack} - {{\underset{\_}{w}}^{H}\underset{\_}{r}}}}^{2} \right\}}} & (5)\end{matrix}$

wherein the weights are represented as w=(w ₁ ^(T) w ₂ ^(T) . . . w _(P)^(T))^(T) in vector form, D represents a decision delay, and thesuperscript H represents a Hermitian operator.

In the abovementioned equation (5), w _(MMSE) can be solved via aWiener-Hopf equation as follow:

w _(MMSE) =R ⁻¹ [H] _(D)  (6),

wherein R is defined as a autocorrelation matrix of the received vectorr, that is, R=E└r·r ^(H)┘. └h┘_(D) resents a vector stacked by theelements of D^(th) columns of H.

According to the equation (6), the weight calculation unit 640calculates the autocorrelation matrix R and its inverse matrix R ⁻¹, andthen multiply the inverse matrix R ⁻¹ with the vector └H┘_(D). Theweight calculation unit 640 may obtain the weights w _(MMSE), that is,all weights that is necessary for the equalizers 660_1˜660_P isobtained. Here, if a better performance of the receiver is required tobe achieved, the D value may be designed to be(F+W−1)·(P−1)+[(F+W−1)/2]. In other words, the elements on the middlecolumns of the matrix H are extracted to compose └H┘_(D). Furthermore,according to the definition of H, when D=(F+W−1)·(P−1)+[(F+W−1)/2],└H┘_(D) is simply obtained by concatenating the middle column of H _(p),which can be represented in equation (7), with p=0, 1, . . . , P−1.

$\begin{matrix}{{\underset{\_}{h}}_{p} = {\left\lbrack {\underset{\underset{\_}{\_}}{H}}_{p} \right\rbrack_{\lfloor{{({F + W - 1})}/2}\rfloor} = {\begin{pmatrix}\underset{\_}{0} \\{\hat{h}\left\lbrack {{pK} + W - 1} \right\rbrack} \\\vdots \\{\hat{h}\left\lbrack {{pK} + 1} \right\rbrack} \\{\hat{h}\lbrack{pK}\rbrack} \\\underset{\_}{0}\end{pmatrix}.}}} & (7)\end{matrix}$

In the abovementioned equation (7), it is assumed that F is larger thanW. h _(p) is defined as a steering vector to represent a vector composedof elements on the ((F+W−1)/2)^(th) column of H _(p). Therefore,according to the value of D defined above, └H┘_(D) can be representedas:

[ H] _(D)=( h _(P) ^(T) . . . h ₂ ^(T) h ₁ ^(T))^(T)=h  (8)

Since the received signals respectively processed by the equalizers660_1˜660_P are interfered from different clusters (Cluster 1˜Cluster P)within the transmission channel, according to the derivation of theequation (6), the channel response of the first to P^(th) clusters aresimultaneously considered and the weights w _(MMSE) are obtained underthe MMSE criterion when calculating the weights corresponding to theequalizers 660_1˜660_P of the present embodiment. However, according tothe equation (6), calculation of the weights requires w _(MMSE) tomultiply the matrix R ⁻¹ with a dimension of FP×FP and the └H┘_(D) withthe dimension of FP×1. Moreover, a large amount of calculation isrequired to be performed for calculating the inverse matrix of R, sothat a calculation complexity during calculation of the weights w_(MMSE) by the weight calculation unit 540 is quite intensive.Therefore, another calculation method of the weights w _(MMSE) isprovided by the present embodiment for decreasing the calculationcomplexity of the weights w _(MMSE).

Since the signal d[m] transmitted from the transmitter is independent,and under the MMSE criterion, the auto correlation matrix R of thereceived vector r may be represented as:

R=HH ^(H)+σ_(v) ² I   (9).

σ_(v) ² represents a variance of the Gaussian noise, and I represents anidentity matrix with a dimension of FP×FP. For conveniently describingthe present embodiment, the equation (9) may be reformulated as:

$\begin{matrix}{\underset{\underset{\_}{\_}}{R} = {\begin{pmatrix}{\underset{\underset{\_}{\_}}{R}}_{0} & {\underset{\underset{\_}{\_}}{R}}_{1}^{H} & \ldots & {\underset{\underset{\_}{\_}}{R}}_{P - 1}^{H} \\{\underset{\underset{\_}{\_}}{R}}_{1} & {\underset{\underset{\_}{\_}}{R}}_{0} & \ddots & {\underset{\underset{\_}{\_}}{R}}_{P - 2}^{H} \\\vdots & \ddots & \ddots & \vdots \\{\underset{\underset{\_}{\_}}{R}}_{P - 1} & {\underset{\underset{\_}{\_}}{R}}_{P - 2} & \ldots & {\underset{\underset{\_}{\_}}{R}}_{0}\end{pmatrix}.}} & (10)\end{matrix}$

The value of the sub-matrices on the diagonal orientation of the matrixR is

${{\underset{\underset{\_}{\_}}{R}}_{0} = {{\sum\limits_{i = 0}^{P - 1}{{\underset{\underset{\_}{\_}}{H}}_{i}{\underset{\underset{\_}{\_}}{H}}_{i}^{H}}} + \sigma_{v}^{2}}},$

and the values of the rest sub-matrices of the matrix R are

${{\underset{\underset{\_}{\_}}{R}}_{p} = {\sum\limits_{i = 0}^{P - p - 1}{{\underset{\underset{\_}{\_}}{H}}_{i}{\underset{\underset{\_}{\_}}{H}}_{i + p}^{H}}}},{p = 1},2,\ldots \mspace{14mu},{P - 1.}$

According to the definition of H _(p), H _(p) is a Toeplitz matrix.Therefore, it can be derived that the structure of the abovementioned R_(p) is banded and R _(p) is the Toeplitz matrix. Based on the documentof note [2], the sub-matrix R _(p) of R may be approximately representedas a circulant matrix S _(p), wherein S _(p) can be decomposed as S_(p)=F ^(H) D _(p) F. In other words, the sub-matrix R _(P) of R may beapproximately represented as:

R _(p)≈F ^(H) D _(p) F  (11).

The matrix D _(p) in the equation (11) is a diagonal matrix, and thevalues thereof is D _(p)=diag{F·[S _(p)]₁}, wherein diag{x} represents adiagonal matrix whose diagonal elements is composed of the element ofthe vector x. [108]₁ represents a vector composed of the first column ofthe matrix. F represents a DFT (Discrete Fourier Transform) matrix,wherein F·a represents to perform DFT to the vector a and F ^(H)·arepresents to perform IDFT (Inverse Discrete Fourier Transform) to thevector a.

Moreover, S _(p) may be a circulant matrix approximated by R _(p). Forexample, R _(p) which is the Toeplitz matrix and has the bandedstructure may be expressed as:

${{\underset{\_}{\underset{\_}{R}}}_{p} = \begin{bmatrix}r_{0} & r_{1} & \cdots & \cdots & r_{W} & 0 & \cdots & \cdots & \cdots & \cdots & \cdots & \cdots & \cdots & 0 \\r_{- 1} & r_{0} & r_{1} & \cdots & \cdots & r_{W} & 0 & \cdots & 0 & 0 & \cdots & \cdots & \cdots & 0 \\r_{- 2} & r_{- 1} & r_{0} & r_{1} & \cdots & \cdots & r_{W} & 0 & \cdots & 0 & 0 & \cdots & \cdots & 0 \\\vdots & \vdots & r_{- 1} & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \vdots \\\vdots & \vdots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & 0 \\r_{- W} & \vdots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & 0 \\0 & r_{- W} & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & 0 \\\vdots & 0 & r_{- W} & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & 0 & \vdots \\\vdots & \ddots & 0 & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & r_{W} & 0 \\\vdots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & r_{W} \\\vdots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \vdots \\\vdots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & r_{1} & \vdots \\\vdots & \ddots & \ddots & \ddots & \ddots & \ddots & 0 & r_{- W} & \ddots & \ddots & \ddots & r_{- 1} & r_{0} & r_{1} \\0 & 0 & \cdots & \cdots & \cdots & \cdots & \cdots & 0 & r_{- W} & \cdots & \cdots & \cdots & r_{- 1} & r_{0}\end{bmatrix}},$

wherein the circulant matrix S _(p) which is approximated by R _(p) isexpressed as:

${\underset{\_}{\underset{\_}{S}}}_{p} = \begin{bmatrix}r_{0} & r_{1} & \cdots & \cdots & r_{W} & 0 & \cdots & 0 & 0 & r_{- W} & r_{{- W} + 1} & \cdots & \cdots & r_{- 1} \\r_{- 1} & r_{0} & r_{1} & \cdots & \cdots & r_{W} & 0 & \cdots & 0 & 0 & r_{- W} & r_{{- W} + 1} & \cdots & r_{- 2} \\r_{- 2} & r_{- 1} & r_{0} & r_{1} & \cdots & \cdots & r_{W} & 0 & \cdots & 0 & 0 & r_{- W} & \ddots & \vdots \\\vdots & \vdots & r_{- 1} & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & r_{{- W} + 1} \\\vdots & \vdots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & r_{- W} \\r_{- W} & \vdots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & 0 \\0 & r_{- W} & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & 0 \\\vdots & 0 & r_{- W} & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & 0 & \vdots \\0 & 0 & 0 & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & r_{W} & 0 \\0 & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & r_{W} \\r_{W} & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \vdots \\\vdots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & \ddots & r_{1} & \vdots \\r_{2} & \ddots & \ddots & \ddots & \ddots & \ddots & 0 & r_{- W} & \ddots & \ddots & \ddots & r_{- 1} & r_{0} & r_{1} \\r_{1} & r_{2} & \cdots & r_{W} & 0 & 0 & \cdots & 0 & r_{- W} & \cdots & \cdots & \cdots & r_{- 1} & r_{0}\end{bmatrix}$

According to the equation (11), the autocorrelation matrix R in theequation (10) can be rewritten as:

$\begin{matrix}\begin{matrix}{\underset{\_}{\underset{\_}{R}} = \begin{pmatrix}{{\underset{\_}{\underset{\_}{F}}}^{H}{\underset{\_}{\underset{\_}{D}}}_{0}\underset{\_}{\underset{\_}{F}}} & {{\underset{\_}{\underset{\_}{F}}}^{H}{\underset{\_}{\underset{\_}{D}}}_{1}^{H}\underset{\_}{\underset{\_}{F}}} & \cdots & {{\underset{\_}{\underset{\_}{F}}}^{H}{\underset{\_}{\underset{\_}{D}}}_{P - 1}^{H}\underset{\_}{\underset{\_}{F}}} \\{{\underset{\_}{\underset{\_}{F}}}^{H}{\underset{\_}{\underset{\_}{D}}}_{1}\underset{\_}{\underset{\_}{F}}} & {{\underset{\_}{\underset{\_}{F}}}^{H}{\underset{\_}{\underset{\_}{D}}}_{0}\underset{\_}{\underset{\_}{F}}} & \ddots & {{\underset{\_}{\underset{\_}{F}}}^{H}{\underset{\_}{\underset{\_}{D}}}_{P - 2}^{H}\underset{\_}{\underset{\_}{F}}} \\\vdots & \ddots & \ddots & \vdots \\{{\underset{\_}{\underset{\_}{F}}}^{H}{\underset{\_}{\underset{\_}{D}}}_{P - 1}\underset{\_}{\underset{\_}{F}}} & {{\underset{\_}{\underset{\_}{F}}}^{H}{\underset{\_}{\underset{\_}{D}}}_{P - 2}\underset{\_}{\underset{\_}{F}}} & \cdots & {{\underset{\_}{\underset{\_}{F}}}^{H}{\underset{\_}{\underset{\_}{D}}}_{0}\underset{\_}{\underset{\_}{F}}}\end{pmatrix}} \\{{= {\left( {\underset{\_}{\underset{\_}{I}} \otimes {\underset{\_}{\underset{\_}{F}}}^{H}} \right){\underset{\_}{\underset{\_}{D}}\left( {\underset{\_}{\underset{\_}{I}} \otimes \underset{\_}{\underset{\_}{F}}} \right)}}},}\end{matrix} & (12)\end{matrix}$

wherein the operator

represent kronecker product, the matrix

$\begin{matrix}{\underset{\_}{\underset{\_}{D}} = {\begin{pmatrix}{\underset{\_}{\underset{\_}{D}}}_{0} & {\underset{\_}{\underset{\_}{D}}}_{1}^{H} & \cdots & {\underset{\_}{\underset{\_}{D}}}_{P - 1}^{H} \\{\underset{\_}{\underset{\_}{D}}}_{1} & {\underset{\_}{\underset{\_}{D}}}_{0} & \ddots & {\underset{\_}{\underset{\_}{D}}}_{P - 2}^{H} \\\vdots & \ddots & \ddots & \vdots \\{\underset{\_}{\underset{\_}{D}}}_{P - 1} & {\underset{\_}{\underset{\_}{D}}}_{P - 2} & \cdots & {\underset{\_}{\underset{\_}{D}}}_{0}\end{pmatrix}.}} & (13)\end{matrix}$

According to the equation (12) and the characteristic of DFT matrix, itcan obtain that the inverse matrix R ⁻¹ of the auto autocorrelationmatrix R can be represented as:

R ⁻¹=( I

F ^(H)) D ⁻¹( I

F )  (14).

In the abovementioned equation (14), I represents a identity matrix withdimension P×P. By substitution of the equation (14) and the equation (8)into the equation (6), the weights w _(MMSE) is:

w _(MMSE)=( I

F ^(H)) D ⁻¹( I

F ) h   (15).

Therefore, in contrast with the equation (6), the equation (15) is moreeasily to implement by hardware, and the amount of calculating theweights w _(MMSE) in the equation (15) is less that in the equation (6).In the abovementioned equation (15), (I

F ^(H)) and (I

F) can be implemented by FFT (Fast Fourier Transform) and IFFT (InverseFast Fourier Transform). However, in the equation (15), it requires tocalculate the inverse matrix D ⁻¹ of D with dimension FP×FP. Forconveniently describing how to calculate the inverse matrix D ⁻¹ in theembodiments of the present invention, P=2 and F=4 are assumed forexample. While P=2 and F=4, the matrix

$\underset{\_}{\underset{\_}{D}} = \begin{pmatrix}{\underset{\_}{\underset{\_}{D}}}_{0} & {\underset{\_}{\underset{\_}{D}}}_{1}^{H} \\{\underset{\_}{\underset{\_}{D}}}_{1} & {\underset{\_}{\underset{\_}{D}}}_{0}\end{pmatrix}$

Can be spread as:

$\underset{\_}{\underset{\_}{D}} = {\begin{pmatrix}D_{0,0} & 0 & 0 & 0 & D_{1,0}^{*} & 0 & 0 & 0 \\0 & D_{0,1} & 0 & 0 & 0 & D_{1,1}^{*} & 0 & 0 \\0 & 0 & D_{0,2} & 0 & 0 & 0 & D_{1,2}^{*} & 0 \\0 & 0 & 0 & D_{0,3} & 0 & 0 & 0 & D_{1,3}^{*} \\D_{1,0} & 0 & 0 & 0 & D_{0,0} & 0 & 0 & 0 \\0 & D_{1,1} & 0 & 0 & 0 & D_{0,1} & 0 & 0 \\0 & 0 & D_{1,2} & 0 & 0 & 0 & D_{0,2} & 0 \\0 & 0 & 0 & D_{1,3} & 0 & 0 & 0 & D_{0,3}\end{pmatrix}.}$

Since each sub-matrix D _(p) of the matrix D is a diagonal matrix, theinverse matrix D ⁻¹ is composed of four sub-matrices, wherein the fourinternal sub-matrices of D ⁻¹ are also diagonal matrices. In otherwords, the inverse matrix D ⁻¹ is obtained as long as the diagonalelements in the four internal sub-matrices of the inverse matrix D ⁻¹are calculated when the inverse matrix D ⁻¹ is calculating. Thus, in thefollowing content, to calculate the diagonal elements of the sub-matrixof D ⁻¹ is described.

First, the first element of each sub-matrix of the matrix D on thediagonal line is extracted to create a particular matrix with dimension2×2, wherein the particular matrix can be represented as:

${\underset{\_}{\underset{\_}{\Lambda}}}_{0} = {\begin{pmatrix}D_{0,0} & D_{1,0}^{*} \\D_{1,0} & D_{0,0}\end{pmatrix}.}$

Next, the inverse matrix Λ ₀ ⁻¹ of the particular matrix Λ ₀ iscalculated. Since the dimension of the particular matrix is 2×2, thevalue of the inverse matrix thereof Λ ₀ ⁻¹ is:

${\underset{\_}{\underset{\_}{\Lambda}}}_{0}^{- 1} = {\begin{pmatrix}D_{0,0} & {- D_{1,0}^{*}} \\{- D_{1,0}} & D_{0,0}\end{pmatrix}/{{\det \left( {\underset{\_}{\underset{\_}{\Lambda}}}_{0} \right)}.}}$

det(Λ ₀) represents the value of determinant of the particular matrix Λ₀. After the inverse matrix Λ ₀ ⁻¹ is solved, the four elements of theinverse matrix Λ ₀ ⁻¹ are respectively served as the first elements ofeach sub-matrix from the inverse matrix D ⁻¹ on the diagonal line.

Afterward, according to the abovementioned method, the second, third andfourth elements of each sub-matrix of the matrix D on the diagonal lineare extracted to create the particular matrices Λ ₁, Λ ₂ and Λ ₃respectively. And then the inverse matrices Λ ₁ ⁻¹, Λ ₂ ⁻¹ and Λ ₃ ⁻¹are calculated. Finally, the respective four element of the inversematrix Λ ₁ ⁻¹, Λ ₂ ⁻¹ and Λ ₃ ⁻¹ are respectively served as the second,third and fourth elements of each sub-matrix from the inverse matrix D⁻¹ on the diagonal line. As the description above, the value the inversematrix D ⁻¹ expressed as the following equation (16).

$\begin{matrix}{{\underset{\_}{\underset{\_}{D}}}^{- 1} = {\begin{pmatrix}\frac{D_{0,0}}{\det \left( {\underset{\_}{\underset{\_}{\Lambda}}}_{0} \right)} & 0 & 0 & 0 & \frac{- D_{1,0}^{*}}{\det \left( {\underset{\_}{\underset{\_}{\Lambda}}}_{0} \right)} & 0 & 0 & 0 \\0 & \frac{D_{0,1}}{\det \left( {\underset{\_}{\underset{\_}{\Lambda}}}_{1} \right)} & 0 & 0 & 0 & \frac{- D_{1,1}^{*}}{\det \left( {\underset{\_}{\underset{\_}{\Lambda}}}_{1} \right)} & 0 & 0 \\0 & 0 & \frac{D_{0,2}}{\det \left( {\underset{\_}{\underset{\_}{\Lambda}}}_{2} \right)} & 0 & 0 & 0 & \frac{- D_{1,2}^{*}}{\det \left( {\underset{\_}{\underset{\_}{\Lambda}}}_{2} \right)} & 0 \\0 & 0 & 0 & \frac{D_{0,3}}{\det \left( {\underset{\_}{\underset{\_}{\Lambda}}}_{3} \right)} & 0 & 0 & 0 & \frac{- D_{1,3}^{*}}{\det \left( {\underset{\_}{\underset{\_}{\Lambda}}}_{3} \right)} \\\frac{- D_{1,0}}{\det \left( {\underset{\_}{\underset{\_}{\Lambda}}}_{0} \right)} & 0 & 0 & 0 & \frac{D_{0,0}}{\det \left( {\underset{\_}{\underset{\_}{\Lambda}}}_{0} \right)} & 0 & 0 & 0 \\0 & \frac{- D_{1,1}}{\det \left( {\underset{\_}{\underset{\_}{\Lambda}}}_{1} \right)} & 0 & 0 & 0 & \frac{D_{0,1}}{\det \left( {\underset{\_}{\underset{\_}{\Lambda}}}_{1} \right)} & 0 & 0 \\0 & 0 & \frac{- D_{1,2}}{\det \left( {\underset{\_}{\underset{\_}{\Lambda}}}_{2} \right)} & 0 & 0 & 0 & \frac{D_{0,2}}{\det \left( {\underset{\_}{\underset{\_}{\Lambda}}}_{2} \right)} & 0 \\0 & 0 & 0 & \frac{- D_{1,3}}{\det \left( {\underset{\_}{\underset{\_}{\Lambda}}}_{3} \right)} & 0 & 0 & 0 & \frac{D_{0,3}}{\det \left( {\underset{\_}{\underset{\_}{\Lambda}}}_{3} \right)}\end{pmatrix}.}} & (16)\end{matrix}$

According to the abovementioned example, it is unnecessary to directlycalculate the matrix D with dimension FP×FP into the inverse matrix D⁻¹. Instead, the matrix D is separated as F particular matrices Λ _(k)with dimension P×P and then the inverse matrices Λ _(k) ⁻¹ of theparticular matrices Λ _(k) is calculated. Therefore, the amount ofcalculating the inverse matrix D ⁻¹ can be reduced. The particularmatrix Λ _(k) can be represented as:

$\begin{matrix}{{\underset{\_}{\underset{\_}{\Lambda}}}_{k} = \begin{pmatrix}{{\underset{\_}{\underset{\_}{D}}}_{0}\lbrack k\rbrack} & {{\underset{\_}{\underset{\_}{D}}}_{1}\lbrack k\rbrack}^{*} & \cdots & {{\underset{\_}{\underset{\_}{D}}}_{P - 1}\lbrack k\rbrack}^{*} \\{{\underset{\_}{\underset{\_}{D}}}_{1}\lbrack k\rbrack} & {{\underset{\_}{\underset{\_}{D}}}_{0}\lbrack k\rbrack} & \ddots & {{\underset{\_}{\underset{\_}{D}}}_{P - 2}\lbrack k\rbrack}^{*} \\\vdots & \ddots & \ddots & \vdots \\{{\underset{\_}{\underset{\_}{D}}}_{P - 1}\lbrack k\rbrack} & {{\underset{\_}{\underset{\_}{D}}}_{P - 2}\lbrack k\rbrack} & \cdots & {{\underset{\_}{\underset{\_}{D}}}_{0}\lbrack k\rbrack}\end{pmatrix}} & (17)\end{matrix}$

wherein D _(p)[k] represents the k^(th) element on the diagonal line inthe sub-matrix D _(p) of the matrix D, where k=1, 2, . . . , F.

According to the abovementioned derivation of the weights, the weightcalculation unit 640 calculates the weights {w ₁, w ₂, . . . , w _(P)}under MMSE criterion. In other words, the weights of the equalizers660_1˜660_P are calculated by the gains of the delay paths from the allclusters in the whole channel. Thus, the equalizers 660_1˜660_P can beused for reducing the interference caused from the different clusters ofthe channel to further improve the performance of the receiver.

FIG. 10 is a system block diagram illustrating the weight calculationunit 640 according to an embodiment of the present invention. Referringto FIG. 10, the weight calculation unit 640 includes steering vectorgeneration units 1010_1˜1010_P, Fourier transform units 1020_1˜1020_P,de-correlators 1030_1˜1030_F, inverse Fourier transform units1040_1˜1040_P, a correlation matrix calculation unit 1050, circulantmatrix generation units 1060_1˜1060_P, Fourier transform units1070_1˜1070_P and a de-correlation matrix unit 1080.

First, the steering vector generation units 1010_1˜1010_Pcorrespondingly receives channel responses estimated based on thesignals extracted by P CE windows of the channel estimation unit 630 andgenerates steering vectors according to the channel responses.Illustrating by the example of the p^(th) steering vector generationunit, the p^(th) steering vector generation unit receives the channelresponse ĥ[pK], ĥ[pK+1], . . . , ĥ[pK+W−1] of the p^(th) CE window andgenerates the steering vector

${\underset{\_}{h}}_{p} = {\begin{pmatrix}\underset{\_}{0} \\{\hat{h}\left\lbrack {{pK} + W - 1} \right\rbrack} \\\vdots \\{\hat{h}\left\lbrack {{pK} + 1} \right\rbrack} \\{\hat{h}\lbrack{pK}\rbrack} \\\underset{\_}{0}\end{pmatrix}.}$

Next, according to the equation (15), the discrete Fourier transformmatrices respectively perform DFT to each of the steering vectors toobtain F·h _(p). Therefore, the Fourier transform units 1020_1˜1020_Prespectively perform DFT to the received steering vector and output Ffrequency components.

In addition, the correlation matrix calculation unit 1050 calculates theautocorrelation matrix R according to the channel response estimated bythe channel estimation unit 630. Afterward, the circulant matrixgeneration units 1060_1˜1060_P respectively calculates the circulantmatrixes S ₀˜S _(P-1) by the sub-matrixes R ₀˜R _(P-1) from theautocorrelation matrix R and respectively extracts the first column ofthe circulant matrixes S ₀˜S _(P-1) to obtain [S ₀]₁˜[S _(P-1)]₁. Next,the Fourier transform units respectively perform DFT to [S ₀]₁˜[S_(P-1)]₁ to obtain diagnol matrices D ₀˜D _(P-1). And then thede-correlation matrix unit 1080 combines the matrices into D ₀˜D _(P-1)into the matrix D according to the abovementioned equation (13).Moreover, according to the derivation of the inverse matrix D ⁻¹ of thematrix D, the de-correlation matrix unit 1080 generates F particularmatrices Λ ₁˜Λ _(F) based on the matrix D and calculates F inversematrices (Λ ₁)⁻¹˜(Λ _(F))⁻¹ from the particular matrices according tothe equation (17), and correspondingly outputs F inverse matrices (Λ₁)⁻¹˜(Λ _(F))⁻¹ to the de-correlators 1030_1˜1030_F wherein thedimension of each inverse matrix (Λ ₁)⁻¹˜(Λ _(F))⁻¹ is P×P.

Afterward, according to the equation (15), the inverse matrix D ⁻¹ hasto multiply F·h outputted from the Fourier transform units1020_1˜1020_P. Since the inverse matrix S ⁻¹ has been decomposed to theinverse matrices (Λ ₁)⁻¹˜Λ _(F))⁻¹, according to the matrixmultiplication of the equation (15), the de-correlator 1030_1 receiveseach first frequency component from the Fourier transform units1020_1˜1020_P, and multiplies the P rows of inverse matrix (Λ ₁)⁻¹ bythe P received first frequency components to output P pieces of sum ofproduct. The de-correlator 1030_2 receives each second frequencycomponents outputted from the Fourier transform units 1020_1˜1020_P, andmultiplies the P rows of inverse matrix (Λ ₂)⁻¹ by the P received secondfrequency components to output P pieces of sum of product. Thede-correlator 1030_F receives each F^(th) frequency components outputtedfrom the Fourier transform units 1020_1˜1020_P, and multiplies the Prows of inverse matrix (Λ _(f))⁻¹ by the P received F^(th) frequencycomponents to output P pieces of sum of product.

According to the equation (15), the inverse Fourier transform unit1040_1 receives each first sum of product outputted from thede-correlator 1030_1˜1030_F and performs the inverse Fourier transformto the received F pieces of sum of product to output the weight w ₁ forthe equalizer 660_1. The inverse Fourier transform unit 1040_2 receiveseach second sum of product outputted from the de-correlator1030_1˜1030_F and performs the inverse Fourier transform to the receivedF pieces of sum of product to output the weight w ₂ for the equalizer660_2. That means, the inverse Fourier transform unit 1040_P receiveseach P^(th) sum of product outputted from the de-correlator1030_1˜1030_F and performs the inverse Fourier transform to the receivedF pieces of sum of product to output the weight w _(P) of the equalizer660_P.

According to the operation of the weight calculation unit 640 in FIG.10, the particular matrix Λ _(k) is introduced in the present embodimentso that the calculation of the inverse matrix D from the matrix D withdimension FP×FP unnecessary in the progress of the operation. Instead,the calculation of the inverse matrix Λ _(k) ⁻¹ of the particular matrixΛ _(k) is operated in the present embodiment. In addition, according tothe operation of the weight calculation unit 640 in FIG. 10, the Fouriertransform units and the inverse Fourier transform units in hardwareimplementation can be implemented by FFT (fast Fourier transform) tofurther reduce the complexity of the calculation of the weights.

One of ordinary skills in the art should know that the above-mentionedembodiments not only can apply to the transmission channel with aplurality of clusters but also apply to the transmission channel withdifferent types. For example, when the transmission channel which hasonly one cluster but with densely-distributed and long-delaymulti-paths, the length of the conventional equalizer is too short tocover the excessive long transmission channel. However, the equalizationapparatus 600 in the abovementioned embodiment can be applied to theabovementioned channel if the window interval K is set to F which is thelength of the equalizer 660_1˜660_P so that the equalizer 660_1˜660_Pare equivalent to an equalizer with the length is KF. In addition, thecorrelation matrix calculation unit 1050 of the weight calculation unit640 is accordingly adjusted. However, the adjustment of the restelements of the equalization apparatus 600 is unnecessary.

FIG. 11 is a system block diagram illustrating a weight calculation unit1100 according to another embodiment of the present invention. Referringto FIG. 11, the elements in the weight calculation unit 1100 are similarto that of the weight calculation unit 640 in FIG. 10 so that thedescription on the same portion is omitted. The difference between theweight calculation unit 1100 and 640 in FIG. 10 is the correlationmatrix calculation unit 1150. The correlation matrix calculation unit1150 calculates and generates the autocorrelation matrix R based on thechannel response estimated by the channel estimation unit 630, whereinR=HH ^(H)+σ_(v) ² I. The value of H is:

$\underset{\_}{\underset{\_}{H}} = {\begin{pmatrix}{\hat{h}\lbrack 0\rbrack} & {\hat{h}\lbrack 1\rbrack} & \cdots & {\hat{h}\left\lbrack {{PW} - 1} \right\rbrack} & 0 & \cdots & 0 \\0 & {\hat{h}\lbrack 0\rbrack} & {\hat{h}\lbrack 1\rbrack} & \ddots & {\hat{h}\left\lbrack {{PW} - 1} \right\rbrack} & \ddots & \vdots \\\vdots & \ddots & \ddots & \ddots & \ddots & \ddots & 0 \\0 & \cdots & 0 & {\hat{h}\lbrack 0\rbrack} & {\hat{h}\lbrack 1\rbrack} & \cdots & {\hat{h}\left\lbrack {{PW} - 1} \right\rbrack}\end{pmatrix} \in {C^{{PF} \times {({{PF} + {PW} - 1})}}.}}$

Therefore, when the delay parameter generating unit 620 determines thetransmission channel to have only one cluster but withdensely-distributed long-delay multi-paths according to the searchingresult of the multi-path searcher 610, the delay parameter generatingunit 620 determines that the window interval K is F. The firmware or thesoftware in the weight calculation unit 640 adjusts the mathematicaloperation of the correlation matrix calculation unit 1150 as well sothat the equalization apparatus 600 can be adapted the present channel.

Moreover, if the receiver has a plurality of receive branches, as longas the cluster delay units 530 in the equalization apparatus 600 shownin FIG. 6 is modified, the equalization apparatus 600 can be applied tothe receiver with the plurality of receive branches. FIG. 12 is a systemblock diagram illustrating an equalization apparatus according toanother embodiment of the present invention. Referring to FIG. 12, theequalization apparatus 1200 is similar to the equalization apparatus 600in FIG. 6, and the multi-path searcher 610, the delay parametergenerating unit 620, the channel estimation unit 630 and the weightcalculation unit 640 in FIG. 6 are similar to those in the equalizationapparatus 1200 so that the abovementioned units are not shown in FIG.12. The difference between the equalization apparatus 1200 and theequalization apparatus 600 in FIG. 6 is the cluster delay unit 1200 inFIG. 12. The cluster delay unit 1250 includes P−1 delay units1251_1˜1251_(P−1) and P−1 switch units 1252_1˜1252_(P−1), the couplingrelationship thereof is shown in FIG. 12. When the input terminal of theswitch units 1252_1˜1252_(P−1) is coupled to the delay units1251_1˜1251_(P−1), the operation of the cluster delay unit 1250 is thesame as the cluster delay unit 530 in FIG. 6. When the receiver has aplurality of receive branches, the input terminals of the switch units1252_1˜1252_(P−1) can be switched to connect to the plurality of receivebranches so that the equalizers 660_1˜660_P respectively receive thereceived signal from the plurality of receive branches.

When the input terminals of the switch units are switched to connect tothe plurality of receive branches, the correlation matrix calculationunit 1050 of the weight calculation unit 640 in FIG. 10 is adjusted.FIG. 13 is a system block diagram illustrating a weight calculation unit1300 according to another embodiment of the present invention. Referringto FIG. 13, since the receiver has the plurality of receive branches,the left side of FIG. 13 illustrates the channel power delay profileobtained from the plurality of receive branches. According to thepositions of the CE windows in FIG. 13, the channel estimation unit 630respectively estimates the received signal of the each of the receivebranches, and elements of the weight calculation unit 1300 are similarto those of the weight calculation unit 640 in FIG. 10. Therefore,description of the same portion is omitted. The difference between theweight calculation unit 1300 and the weight calculation unit 640 is thecorrelation matrix calculation unit 1350. The correlation matrixcalculation unit 1350 calculates the autocorrelation matrix R based onthe channel response estimated by the channel estimation unit 630,wherein R=HH ^(H)+σ_(v) ² I. The value of H is:

${\underset{\_}{\underset{\_}{H}} = {\begin{pmatrix}{\underset{\_}{\underset{\_}{H}}}_{1} \\{\underset{\_}{\underset{\_}{H}}}_{2} \\\vdots \\{\underset{\_}{\underset{\_}{H}}}_{P}\end{pmatrix} \in C^{{PF} \times {({F + W - 1})}}}},$

wherein the sub-matrix H _(p) of the matrix H represents the matrixcomposed of the estimated result which is estimated based on thereceived signal from the p^(th) receive branch, and the value of H _(p)is:

${\underset{\_}{\underset{\_}{H}}}_{p} = {\begin{pmatrix}{{\hat{h}}_{p}\lbrack 0\rbrack} & {{\hat{h}}_{p}\lbrack 1\rbrack} & \cdots & {{\hat{h}}_{p}\left\lbrack {W - 1} \right\rbrack} & 0 & \cdots & 0 \\0 & {{\hat{h}}_{p}\lbrack 0\rbrack} & {{\hat{h}}_{p}\lbrack 1\rbrack} & \ddots & {{\hat{h}}_{p}\left\lbrack {W - 1} \right\rbrack} & \ddots & \vdots \\\vdots & \ddots & \ddots & \ddots & \ddots & \ddots & 0 \\0 & \cdots & 0 & {{\hat{h}}_{p}\lbrack 0\rbrack} & {{\hat{h}}_{p}\lbrack 1\rbrack} & \cdots & {{\hat{h}}_{p}\left\lbrack {W - 1} \right\rbrack}\end{pmatrix} \in {C^{F \times {({F + W - 1})}}.}}$

According to the operation of the equalization apparatus 505 in FIG. 5,a equalization method is provided as shown in FIG. 14. FIG. 14 is aflowchart illustrating an equalization method according to an embodimentof the present invention. Referring to FIG. 14, the method includes thesteps as follow.

In step S1401, the equalization method starts.

In step S1402, the received signal from the transmitter through thetransmission channel is received. The transmission channel has aplurality of delay paths, and each delay path has at least P clusters.

In step S1403, the gains of the delay paths corresponding to the Pclusters are estimated.

In step S1404, a MMSE algorithm to the gains of the delay pathscorresponding to the P clusters is performed to obtain a plurality offirst to P^(th) weights {w ₁, w ₂, . . . , w _(P)}. The abovementionedMMSE algorithm can be represented as equation (2), and the weights {w ₁,w ₂, . . . , w _(P)} can be solved by an adaptive approach or a directmatrix inversion.

In step S1405, the received signal is respectively delayed for K₁, K₂,K₃ . . . K_(P) unit time to obtain a plurality of cluster delay signalsr[m−K₁], r[m−K₂], r[m−K₃] . . . r[m−K_(P)]. The abovementioned timeparameter K₁, K₂, K₃ . . . K_(P) are determined based on the delay timeof each cluster which is estimated by channel estimation technology orthe delay time of each delay path which is scanned by a multi-pathsearcher.

In step S1406, the cluster delay signals r[m−K₁], r[m−K₂], r[m−K₃] . . .r[m−K_(P)] are received and the received cluster delay signals r[m−K₁],r[m−K₂], r[m−K₃] . . . r[m−K_(P)] is equalized according to the first toP^(th) weights {w ₁, w ₂, . . . , w _(P)} to obtain the first to P^(th)equalized signals. The abovementioned equalizing operation may be shownas FIG. 9.

In step S1407, the first to P^(th) equalized signals are combined and aequalized signal is outputted. The abovementioned equalized signal maybe obtained by directly adding the first equalized signal to the P^(th)equalized signal or by adding the first equalized signal to the P^(th)equalized signal respectively with preset proportions.

In step S1408, the equalization method ends.

According to the operation of the equalization apparatus 600 in FIG. 6,the equalization method is provided as shown in FIG. 5. FIG. 15 is aflowchart illustrating an equalization method according to anotherembodiment of the present invention. Referring to FIG. 15, the methodincludes the steps as follow.

In step S1501, the equalization method starts.

In step S1502, the received signal from the transmitter through thetransmission channel is received. The transmission channel has aplurality of delay paths, and the delay paths are at least with Pclusters.

In step S1503, the delay paths of the transmission channel and the delaytime of the delay paths is searched. The abovementioned step S1503 maybe implemented by a multi-path searcher.

In step S1504, the number P of the cluster of the delay paths isdetermined according to the delay time of the delay paths and a windowinterval K is determined according to the interval of the clusters andthe initial delay time of the clusters. In the abovementioned stepS1504, the number P of the cluster and the window interval K may bedetermined by the abovementioned steps in FIG. 8.

In step S1505, channel estimation is performed to P cluster in thetransmission channel by P CE windows. The position of the P channelestimation windows in the channel power delay profile may be shown inFIG. 7, wherein the channel response obtained from the p^(th) channelestimation window is represented as ĥ[_(p)K], ĥ[pK+1], . . . ,ĥ[pK+W−1].

In step S1506, a MMSE algorithm is performed to calculate a plurality offirst weights to a plurality of P^(th) weights {w ₁, w ₂, . . . , w_(P)} according to the channel response estimated by channel estimation.The equation (6) or the equation (15) can be used for calculating theweights. When the equation (15) is used for calculating the weights {w₁, w ₂, . . . , w _(P)}, the step S1506 includes the following steps.FIG. 16 is a flowchart illustrating the sub-step of the step S1506according to another embodiment of the present invention. Referring toFIG. 16, the step S1506 includes the steps as follow.

In step S1602, P steering vectors is composed according to the channelresponse by performing the channel estimation from the P channelestimation windows, wherein the definition of steer vector is as theequation (7).

In step S1603, a discrete Fourier transform is performed to eachsteering vector, wherein performing the discrete Fourier transform tothe p^(th) steering vector h _(p) obtains a transforming result F·h_(p), wherein the transforming result F·h _(p) has F frequencycomponents. The abovementioned step S1603 may be the operation of theFourier transform units 1020_1˜1020_P in FIG. 10.

In step S1604, the auto-correlation matrix R is generated by the channelresponse obtained from the channel estimation, wherein the definition ofthe auto-correlation matrix R may be as the equation (10).

In step S1605, the circulant matrixes S ₀˜S _(P-1) which areapproximated to the sub-matrixes R ₀˜R _(P-1) from auto-correlationmatrix R are generated and the elements [S ₀]₁˜[S _(P-1)] on the firstcolumn of the circulant matrixes S ₀˜S _(P-1) are extracted.

In step S1606, a discrete Fourier transform is performed to the elements[S ₀]₁˜[S _(P-1)]₁ to obtain the diagonal matrix D ₀˜D _(P-1), whereinthe p^(th) diagonal matrix is represented as D _(p)=diag{F·[S _(p)]₁}.

In step S1607, the matrix D is composed according to the diagonal matrixD ₀˜D _(P-1) wherein the matrix D is defined as the equation (13) forexample.

In step S1608, F particular matrixes Λ ₁˜Λ _(F) are respectivelygenerated according to the matrix D and the inverse matrixes (Λ ₁)⁻¹˜(Λ_(F))⁻¹ of the particular matrixes are calculated, wherein theparticular matrices are defined as equation (17) for example.

In step S1609, a de-correlation operation is performed for F times. Theabovementioned de-correlation operation may be implemented by theoperation of the de-correlators 1030_1˜1030_F in FIG. 10, wherein i^(th)de-correlation operation receives each of the i^(th) frequency componentof the discrete Fourier transform F·h _(p) and correspondinglymultiplies P frequency components to the elements on the p^(th) row ofthe matrix (Λ _(i))⁻¹ to output P pieces of sum of product, wherein i=1,2, . . . , F.

In step S1610, an inverse discrete Fourier transform is performed for Ptimes. The abovementioned inverse discrete Fourier transform may beimplemented by the operation of the inverse discrete Fourier transformunit 1040_1˜1040_P, wherein the j^(th) inverse discrete Fouriertransform receives the j^(th) sum of product obtained from eachde-correlation operation, and performs the inverse discrete Fouriertransform to received F pieces of sum of product to output the weight w_(j), wherein j=1, 2, . . . , P.

Referring to FIG. 15, the method further includes the step as follow.

In step S1507, the received signal r[m] is sequentially delayed for Kunit time to obtain the cluster delay signals r[m], r[m−K], r[m−2K], . .. , r[m−(P−1)K]. The abovementioned step S1507 may be implemented by theoperation of the cluster delay unit 650 in FIG. 6.

In step S1508, the cluster delay signals r[m], r[m−K], r[m−2K], . . . ,r[m−(P−1)K] is equalized according to the first to P^(th) weights {w ₁,w ₂, . . . , w _(P)} to obtain an first to P^(th) equalized signal. Theabovementioned equalizing operation may be implemented by the operationin FIG. 9.

In step S1509, the first to P^(th) equalized signals are combined and aequalized signal is outputted. The abovementioned equalized signal maybe obtained by directly adding the first equalized signal to the P^(th)equalized signal or by adding the first equalized signal to the P^(th)equalized signal respectively with preset proportions.

In step S1510, the equalization method ends.

In summary, the present invention includes at least the followingadvantages.

First, a plurality of equalizers is adopted for equalizing receivedsignals corrupted by the channel with delay paths from differentclusters. Meanwhile, the weights of the plurality of equalizers iscalculated under MMSE criterion according to the gain of the wholechannel so as to reduce the interference caused by the delay paths ofthe different clusters in whole channel.

Second, the received signal is sequentially delayed for K unit time andthen the delayed signals are correspondingly outputted to the pluralityof equalizers. Therefore, the cluster delay unit 530 in the presentembodiment can be equivalently for extending the length of theequalization apparatus so that the interference of the transmissionchannel with the large delay spread can be eliminated by theequalization apparatus.

Third, the particular matrix Λ _(k) is advised in the present inventionso that the calculation of the inverse matrix D ⁻¹ from the matrix Dwith dimension FP×FP are unnecessary in the progress of the weightcalculation, instead, the inverse matrix Λ _(k) ⁻¹ of the particularmatrix Λ _(k) is calculated. Therefore, the present invention cangreatly reduces the complexity of weight calculation. Moreover, when thepresent embodiment is actually applied to hardware, the weightcalculation can be implemented by FFT (fast Fourier transform) algorithmso as to further reduce the complexity of hardware implementation.

While the invention has been described by way of examples and in termsof preferred embodiments, it is to be understood that the invention isnot limited thereto. To the contrary, it is intended to cover variousmodifications. Therefore, the scope of the appended claims should beaccorded the broadest interpretation so as to encompass all suchmodifications.

Note [2]: Zhang, J. Bhatt, T. and Mandyam, G., “Efficient LinearEqualization for High Data Rate Downlink CDMA Signaling,” proc. of 37thIEEE Asilomar Conference on signals, Systems, and computers, Monterey,Calif., pp. 141-145, vol. 1, November 2003.

1. An equalization apparatus for receiving a received signal from atransmitter via a transmission channel in wireless communication,wherein the transmission channel has a plurality of delay paths, and thedelay paths are grouped into P clusters, the equalization apparatuscomprising: a channel estimation unit, for estimating gains of the delaypaths corresponding to the P clusters; a weight calculation unit, forperforming a minimum mean square error (MMSE) algorithm to the gains ofthe delay paths corresponding to the P clusters, so as to obtain aplurality of N^(th) weights, wherein N=1, 2, . . . , P; a cluster delayunit, for generating a plurality of cluster delayed signals by delayingthe received signal for K₁, K₂, K₃, . . . K_(P) unit time, wherein thereceived signal is represented as r[m], and the cluster delayed signalsare respectively represented as r[m−K₁], r[m−K₂], r[m−K₃] . . . ,r[m−K_(P)], wherein “m” is represented as a time index; P equalizers,for equalizing the cluster delayed signals r[m−K₁], r[m−K₂], r[m−K₃] . .. , r[m−K_(P)] to obtain an N^(th) equalized signals according to theN^(th) weights; and a combination unit, for combining the N^(th)equalized signals to a equalized signal, wherein P is larger than 2, andP, K₁, K₂, K₃, . . . , K_(P) and m are positive integers.
 2. Theequalization apparatus according to claim 1, further comprising: amulti-path searcher, for searching the delay paths from the transmissionchannel and corresponding delay time.
 3. The equalization apparatusaccording to claim 1, further comprising: a delay parameter generatingunit, for determining number of the cluster of the delay paths accordingto the corresponding delay time and determining a window intervalaccording to an interval and an initial delay time of the clusters. 4.The equalization apparatus according to claim 3, wherein the windowinterval is represented as K, and the number of the cluster isrepresented as P, and the cluster delay unit sequentially delays thereceived signal r[m] for K unit time to generate the cluster delayedsignals r[m], r[m−K], r[m−2K], r[m−(P−1)K].
 5. The equalizationapparatus according to claim 4, wherein the channel estimation unit hasP channel estimation windows, length of the channel estimation windowsare respectively represented as W, the channel response of p^(th)channel estimation window estimated by the channel estimation unit isrepresented as ĥ[pK], ĥ[pK+1], . . . , ĥ[pK+W−1], where p=0, 1, . . . ,P−1, the number of each weights is F, the weights are represented asw=(w ₁ ^(T) w ₂ ^(T) . . . w _(P) ^(T))^(T), wherein the p^(th) weightsis represented as w _(p)=[w_(p,0) w_(p,1) . . . w_(p,F-1)]^(T), theweight calculation unit calculates the weights w=(w ₁ ^(T) w ₂ ^(T) . .. w _(P) ^(T))^(T) by the equation w=R ⁻¹[H]_(D), wherein R representsan autocorrelation matrix of a received vector r, the autocorrelationmatrix R=E└r·r ^(H)┘, the received vector${\underset{\_}{r} = \begin{pmatrix}{\underset{\_}{r}\lbrack m\rbrack} \\{\underset{\_}{r}\left\lbrack {m - K} \right\rbrack} \\\vdots \\{\underset{\_}{r}\left\lbrack {m - {\left( {P - 1} \right)K}} \right\rbrack}\end{pmatrix}},$ wherein the sub-vector of the received vectorr[m]=(r[m] r[m−1] . . . r[m−F+1])^(T), the matrix${\underset{\underset{\_}{\_}}{H} = \begin{pmatrix}{\underset{\underset{\_}{\_}}{H}}_{0} & {\underset{\underset{\_}{\_}}{H}}_{1} & \cdots & {\underset{\underset{\_}{\_}}{H}}_{p - 1} & 0 & \cdots & 0 \\0 & {\underset{\underset{\_}{\_}}{H}}_{0} & {\underset{\underset{\_}{\_}}{H}}_{1} & \cdots & {\underset{\underset{\_}{\_}}{H}}_{0} & \ddots & \vdots \\\vdots & \ddots & \ddots & \ddots & \ddots & \ddots & 0 \\0 & \cdots & 0 & {\underset{\underset{\_}{\_}}{H}}_{0} & {\underset{\underset{\_}{\_}}{H}}_{1} & \cdots & {\underset{\underset{\_}{\_}}{H}}_{P - 1}\end{pmatrix}},$ wherein the sub-matrix of H is${{\underset{\underset{\_}{\_}}{H}}_{p} = {\begin{pmatrix}{\hat{h}\lbrack{pK}\rbrack} & {\hat{h}\left\lbrack {{pK} + 1} \right\rbrack} & \cdots & {\hat{h}\left\lbrack {{pK} + W - 1} \right\rbrack} & 0 & \cdots & 0 \\0 & {\hat{h}\lbrack{pK}\rbrack} & {\hat{h}\left\lbrack {{pK} + 1} \right\rbrack} & \ddots & {\hat{h}\left\lbrack {{pK} + W - 1} \right\rbrack} & \ddots & \vdots \\\vdots & \ddots & \ddots & \ddots & \ddots & \ddots & 0 \\0 & \cdots & 0 & {\hat{h}\lbrack{pK}\rbrack} & {\hat{h}\left\lbrack {{pK} + 1} \right\rbrack} & \cdots & {\hat{h}\left\lbrack {{pK} + W - 1} \right\rbrack}\end{pmatrix} \in C^{{Fx}{({F + W - 1})}}}},$ [H]_(D) represents avector stacked by elements of D^(th) column of H, D is a decision delay,the value of the decision delay D is (F+W−1)·(P−1)+[(F+W−1)/2].
 6. Theequalization apparatus according to claim 5, wherein the weightcalculation unit calculates the N^(th) weights according to the equationw=(I

F ^(H))D ⁻¹(I

F)[H]_(D), wherein I represents an identity matrix with the dimension ofP×P, F represents a discrete Fourier transform (DFT) matrix, the matrix${\underset{\underset{\_}{\_}}{D} = \begin{pmatrix}{\underset{\underset{\_}{\_}}{D}}_{0} & {\underset{\underset{\_}{\_}}{D}}_{1}^{H} & \cdots & {\underset{\underset{\_}{\_}}{D}}_{P - 1}^{H} \\{\underset{\underset{\_}{\_}}{D}}_{1} & {\underset{\underset{\_}{\_}}{D}}_{0} & \ddots & {\underset{\underset{\_}{\_}}{D}}_{P - 2}^{H} \\\vdots & \ddots & \ddots & \vdots \\{\underset{\underset{\_}{\_}}{D}}_{P - 1} & {\underset{\underset{\_}{\_}}{D}}_{P - 2} & \cdots & {\underset{\underset{\_}{\_}}{D}}_{0}\end{pmatrix}},$ where the matrix D comprises P−1 diagonal matrixes D₀˜D _(P-1), the p^(th) diagonal matrix D _(p)=diag{F·[S _(p)]₁}, diag{x}represents a diagonal matrix, the diagonal elements thereof are composedof elements of a vector x, S _(p) is a circulant matrix approximated bythe sub-matrix R _(p) of the autocorrelation matrix R, where${\underset{\underset{\_}{\_}}{R} = \begin{pmatrix}{\underset{\underset{\_}{\_}}{R}}_{0} & {\underset{\underset{\_}{\_}}{R}}_{1}^{H} & \cdots & {\underset{\underset{\_}{\_}}{R}}_{P - 1}^{H} \\{\underset{\underset{\_}{\_}}{R}}_{1} & {\underset{\underset{\_}{\_}}{R}}_{0} & \ddots & {\underset{\underset{\_}{\_}}{R}}_{P - 2}^{H} \\\vdots & \ddots & \ddots & \vdots \\{\underset{\underset{\_}{\_}}{R}}_{P - 1} & {\underset{\underset{\_}{\_}}{R}}_{P - 2} & \cdots & {\underset{\underset{\_}{\_}}{R}}_{0}\end{pmatrix}},$ the sub-matrix on the diagonal line of theautocorrelation matrix R is represented as${{\underset{\underset{\_}{\_}}{R}}_{0} = {{\sum\limits_{i = 0}^{P - 1}{{\underset{\underset{\_}{\_}}{H}}_{i}{\underset{\underset{\_}{\_}}{H}}_{i}^{H}}} + \sigma_{v}^{2}}},$the rest sub-matrix thereof is represented as${{\underset{\underset{\_}{\_}}{R}}_{p} = {\sum\limits_{i = 0}^{P - p - 1}{{\underset{\underset{\_}{\_}}{H}}_{i}{\underset{\underset{\_}{\_}}{H}}_{i + p}^{H}}}},{p = 1},2,\ldots \mspace{14mu},{P - 1},$wherein the superscript H represents a Hermitian operation, σ_(v) ²represents a variance of a Gaussian noise.
 7. The equalization apparatusaccording to claim 6, wherein the weight calculation unit comprises: Psteering vector generation units, for correspondingly receiving theestimated channel responses, which are estimated by a signal acquired bythe P channel estimation windows of the channel estimation unit, togenerate P steering vectors; P Fourier transform units, for performingthe Fourier transform to the steering vectors to output F frequencycomponents; a correlation matrix calculation unit, for generating theautocorrelation matrix R according to the channel response estimated bythe channel estimation unit; P circulant matrix generation units, forcalculating the circulant matrixes S ₀˜S _(P-1) respectively similar tothe sub-matrixes R ₀˜R _(P-1) of the autocorrelation matrix R andextracting the first column of the circulant matrixes S ₀˜S _(P-1) torespectively output [S ₀]₁˜[S _(P-1)]₁; P Fourier transform units, forperforming the discrete Fourier transform to [S ₀]₁˜[S _(P-1)]₁ toobtain the diagonal matrixes D ₀˜D _(P-1); a de-correlation matrix unit,for generating a matrix D composed of the diagonal matrixes and D ₀˜D_(P-1) and generating F particular matrixes Λ ₁˜Λ _(F) according to thematrix D, and then calculating the inverse matrixes of the particularmatrixes (Λ ₁)⁻¹˜(Λ _(F))⁻¹, wherein the k^(th) particular matrixes isrepresented as${{\underset{\underset{\_}{\_}}{\Lambda}}_{k} = \begin{pmatrix}{{\underset{\underset{\_}{\_}}{D}}_{0}\lbrack k\rbrack} & {{\underset{\underset{\_}{\_}}{D}}_{1}\lbrack k\rbrack}^{*} & \cdots & {{\underset{\underset{\_}{\_}}{D}}_{P - 1}\lbrack k\rbrack}^{*} \\{{\underset{\underset{\_}{\_}}{D}}_{1}\lbrack k\rbrack} & {{\underset{\underset{\_}{\_}}{D}}_{0}\lbrack k\rbrack} & \ddots & {{\underset{\underset{\_}{\_}}{D}}_{P - 2}\lbrack k\rbrack}^{*} \\\vdots & \ddots & \ddots & \vdots \\{{\underset{\underset{\_}{\_}}{D}}_{P - 1}\lbrack k\rbrack} & {{\underset{\underset{\_}{\_}}{D}}_{P - 2}\lbrack k\rbrack} & \cdots & {{\underset{\underset{\_}{\_}}{D}}_{0}\lbrack k\rbrack}\end{pmatrix}},$ D _(p)[k] represents the k^(th) element on the diagonalline of the diagonal matrix D _(p), where k=1, 2, . . . , F; Fde-correlators, correspondingly receiving the inverse matrixes of the Fparticular matrixes (Λ ₁)⁻¹˜(Λ _(F))⁻¹ wherein the i^(th) de-correlatorreceives the i^(th) frequency component from the Fourier transformunits, and respectively multiplies P pieces of the received frequencycomponents by elements of the P^(th) row from the matrix (Λ _(i))⁻¹ tooutput P pieces of sum of product, where i=1, 2, . . . , F; P inverseFourier transform units, wherein the j^(th) inverse Fourier transformunit receives the j^(th) sum of product from the de-correlators andperforms the inverse Fourier transform to F pieces of the received sumof product to output the weights w _(j), where j=1, 2, . . . , P.
 8. Theequalization apparatus according to claim 4, wherein the cluster delayunit further comprises (P−1) delay units, and the delay unitsrespectively including an input terminal and an output terminal, wherethe input terminal of the 1^(st) delay unit receives the received signalr[m], the input terminal of the u^(th) delay unit is coupled to theoutput terminal of the (u−1)^(th) delay unit, where u=2, . . . , P−1,and each said delay unit respectively delays the signal received fromthe input terminal thereof for K unit time.
 9. The equalizationapparatus according to claim 4, wherein the equalization apparatusreceives the received signals from P diversity branches, and the clusterdelay unit comprises: (P−1) delay units, for delaying the signal for Kunit time; and (P−1) switch units, respectively having a first inputterminal, a second input terminal and an output terminal, wherein thefirst input terminal of the v^(th) switch unit is coupled to a(v+1)^(th) diversity antenna, the second input terminal of the v^(th)switch unit is coupled to the output terminal of the v^(th) delay unit,the output terminal of the v^(th) switch unit outputs the correspondingcluster delay signal, and v=1, 2, . . . , P−1.
 10. The equalizationapparatus according to claim 4, wherein the number of p^(th) weights isF, the p^(th) weights are respectively represented as w_(p,0), w_(p,1),. . . , w_(p,F-1), where p=0, 1, . . . , P−1, the equalizersrespectively comprise: (F−1) time delay apparatuses, respectivelycomprising an input terminal and an output terminal, wherein the inputterminal of the 1^(st) time delay apparatus receives the cluster delaysignal r[m−(p−1)K], and the input terminal of the y^(th) time delayapparatus is coupled to the output terminal of the (y−1)^(th) time delayapparatus, for delaying the signal received thereof for a unit time,where y=2, 3, . . . , F−1; F multiplication units, respectivelycomprising a first input terminal, a second input terminal and an outputterminal, wherein the first terminal of the 1^(st) multiplication unitreceives the said cluster delay signal r[m−(p−1)K], the first terminalof the z^(th) multiplication unit is coupled to the output terminal ofthe (z−1)^(th) multiplication unit, where z=2, 3, . . . , F, and thesecond terminals of the multiplication units respectively receive thep^(th) weights, wherein the second terminal of the g^(th) multiplicationunit receives the weight w_(p,g-1) of the p^(th) weights, where g=1, 2,. . . , F, for calculating a multiplication of the received signal fromthe first input terminal thereof and the conjugate transpose of theweight from the second terminal thereof; and an adder, for receiving thesignals from the multiplication units to obtain the p^(th) equalizingsignal.
 11. A equalization method applied in a wireless communication,wherein a transmission channel of the wireless communication is used totransmit a received signal, the transmission channel comprises aplurality of delay paths, the delay paths are grouped into P clusters,the equalization method comprises: estimating gains of the delay pathscorresponding to the P clusters; performing an minimum mean square error(MMSE) algorithm to the gains of the delay paths corresponding to the Pclusters to obtain a plurality of N^(th) weights; delaying the receivedsignal for K_(N) unit time respectively to obtain a plurality of clusterdelay signals, wherein the received signal is represented as r[m], wherem is represented as a time index, wherein the cluster delay signals arerespectively represented as r[m−K_(N)] respectively; equalizing thecluster delay signals according to the N^(th) weights to obtain anN^(th) equalized signal; and combining the N^(th) equalized signal to aequalized signal; wherein P is a nature number, and P is larger than 2,and K_(N) and m are integer, where N=1˜P.
 12. The equalization methodaccording to claim 11, further comprising: searching the delay pathsfrom the transmission channel and corresponding delay time; anddetermining a number of the clusters of the delay paths according to thecorresponding delay time and determining a window interval according toan interval and an initial delay time of the clusters.
 13. Theequalization method according to claim 12, wherein the delay time of thei^(th) path from the transmission channel is represented as D_(i), andthe step of determining the window interval comprises: a). setting theinitial value of i to 1; b). calculating a difference between D_(i) andD_(i-1); c). determining whether difference between D_(i) and D_(i-1) islarger than a threshold value, if the determination is positive,performing the step d) and the step e), otherwise, skipping the step d)and performing the step e); d) adding 1 to a cluster number counterrepresented as CN, and setting the delay time of the 1^(st) delay pathof a CN^(th) cluster to D_(i); e) determining whether all delay pathsare searched, if the determination is negative, performing the step f)and going back to the step b), otherwise performing the step g); f)adding 1 to i; and g) determining the window interval according to thedelay time of the 1^(st) delay path of the cluster corresponding to eachcluster number counter.
 14. The equalization method according to claim12, wherein the window interval is represented as K, the number of theclusters of the delay paths is represented as P and said K_(N)=(N−1)K,where N=1˜P, the step of obtaining the plurality of cluster delaysignals comprises: sequentially delay the received signal r[m] for Kunit time to obtain the cluster delay signals r[m−K_(N)].
 15. Theequalization method according to claim 14, further comprising: providingP channel estimation windows, wherein the length of the channelestimation windows is represented as W, and the interval of the adjacentchannel estimation windows is K unit time; wherein the step ofestimating gains corresponding to the delay paths further comprises:performing the channel estimation to the P clusters from thetransmission channel by the P channel estimation windows, wherein thechannel response obtained from the p^(th) channel estimation window isrepresented as ĥ[pK], ĥ[pK+1], . . . , ĥ[pK+W−1], where p=0, 1, . . . ,P−1.
 16. The equalization method according to claim 15, wherein a numberof the N^(th) weights is F and the N^(th) weights is represented as w=(w₁ ^(T) w ₂ ^(T) . . . w _(P) ^(T))^(T), where w _(p)=[w_(p,0) w_(p,1) .. . w_(p,F-1)]^(T), the step of performing the MMSE algorithm to thegains corresponding to the delay paths of the P clusters to obtain theplurality of N^(th) weights w=(w ₁ ^(T) w ₂ ^(T) . . . w _(P) ^(T))^(T)comprises: calculating the N^(th) weights by utilizing the equation w=R⁻¹[H]_(D); wherein R is represented as an auto correlation matrix of areceived vector r, where R=E└r·r ^(H)┘, the equation of the receivedvector r is represented as ${\underset{\_}{r} = \begin{pmatrix}{\underset{\_}{r}\lbrack m\rbrack} \\{\underset{\_}{r}\left\lbrack {m - k} \right\rbrack} \\\vdots \\{\underset{\_}{r}\left\lbrack {m - {\left( {P - 1} \right)K}} \right\rbrack}\end{pmatrix}},$ wherein the sub-vector of the received vector r isrepresented as r[m]=(r[m] r[m−1] . . . r[m−F+1])^(T),${\underset{\underset{\_}{\_}}{H} = \begin{pmatrix}{\underset{\underset{\_}{\_}}{H}}_{0} & {\underset{\underset{\_}{\_}}{H}}_{1} & \cdots & {\underset{\underset{\_}{\_}}{H}}_{P - 1} & 0 & \cdots & 0 \\0 & {\underset{\underset{\_}{\_}}{H}}_{0} & {\underset{\underset{\_}{\_}}{H}}_{1} & \cdots & {\underset{\underset{\_}{\_}}{H}}_{P - 1} & \ddots & \vdots \\\vdots & \ddots & \ddots & \ddots & \ddots & \ddots & 0 \\0 & \cdots & 0 & {\underset{\underset{\_}{\_}}{H}}_{0} & {\underset{\underset{\_}{\_}}{H}}_{1} & \cdots & {\underset{\underset{\_}{\_}}{H}}_{P - 1}\end{pmatrix}},$ wherein the equation of the sub-matrix of the matrix His represented as${\underset{\underset{\_}{\_}}{H}}_{p} = {\begin{pmatrix}{\hat{h}\lbrack{pK}\rbrack} & {\hat{h}\left\lbrack {{pK} + 1} \right\rbrack} & \cdots & {\hat{h}\left\lbrack {{pK} + W - 1} \right\rbrack} & 0 & \cdots & 0 \\0 & {\hat{h}\lbrack{pK}\rbrack} & {\hat{h}\left\lbrack {{pK} + 1} \right\rbrack} & \ddots & {\hat{h}\left\lbrack {{pK} + W - 1} \right\rbrack} & \ddots & \vdots \\\vdots & \ddots & \ddots & \ddots & \ddots & \ddots & 0 \\0 & \cdots & 0 & {\hat{h}\lbrack{pK}\rbrack} & {\hat{h}\left\lbrack {{pK} + 1} \right\rbrack} & \cdots & {\hat{h}\left\lbrack {{pK} + W - 1} \right\rbrack}\end{pmatrix} \in C^{{Fx}{({F + W - 1})}}}$ where [H]_(D) representsthe vector in the D^(th) column of the matrix H, D is a decision delay,and the value of D is represent as the equationD=(F+W−1)·(P−1)+[(F+W−1)/2].
 17. The equalization method according toclaim 16, wherein the step of performing the MMSE algorithm to the gainscorresponding to the delay paths of the P clusters to obtain theplurality of N^(th) weights w=(w ₁ ^(T) w ₂ ^(T) . . . w _(P) ^(T))^(T)comprises: calculating the N^(th) weights w=w ₁ ^(T) w ₂ ^(T) . . . w_(P) ^(T)) by utilizing the equation w=(I

F ^(h))D ⁻¹(I

F)[H]_(D), wherein I represents identity matrix with dimension P×P, Frepresent a discrete Fourier transform matrix, and the matrix D isrepresented as ${\underset{\underset{\_}{\_}}{D} = \begin{pmatrix}{\underset{\underset{\_}{\_}}{D}}_{0} & {\underset{\underset{\_}{\_}}{D}}_{1}^{H} & \cdots & {\underset{\underset{\_}{\_}}{D}}_{P - 1}^{H} \\{\underset{\underset{\_}{\_}}{D}}_{1} & {\underset{\underset{\_}{\_}}{D}}_{0} & \ddots & {\underset{\underset{\_}{\_}}{D}}_{P - 2}^{H} \\\vdots & \ddots & \ddots & \vdots \\{\underset{\underset{\_}{\_}}{D}}_{P - 1} & {\underset{\underset{\_}{\_}}{D}}_{P - 2} & \cdots & {\underset{\underset{\_}{\_}}{D}}_{0}\end{pmatrix}},$ where the matrix D comprises P−1 diagonal matrixes D₀˜D _(P-1), wherein p^(th) diagonal matrix is represented as D_(p)=diag{F·[S _(p)]₁}, the equation diag{x} represents a diagonalmatrix, wherein the diagonal elements thereof are composed of elementsof a vector x, wherein the matrix S _(p) is a circulant matrix similarto the sub-matrix r _(p) of the said autocorrelation matrix R,${\underset{\underset{\_}{\_}}{R} = \begin{pmatrix}{\underset{\underset{\_}{\_}}{R}}_{0} & {\underset{\underset{\_}{\_}}{R}}_{1}^{H} & \cdots & {\underset{\underset{\_}{\_}}{R}}_{P - 1}^{H} \\{\underset{\underset{\_}{\_}}{R}}_{1} & {\underset{\underset{\_}{\_}}{R}}_{0} & \ddots & {\underset{\underset{\_}{\_}}{R}}_{P - 2}^{H} \\\vdots & \ddots & \ddots & \vdots \\{\underset{\underset{\_}{\_}}{R}}_{P - 1} & {\underset{\underset{\_}{\_}}{R}}_{P - 2} & \cdots & {\underset{\underset{\_}{\_}}{R}}_{0}\end{pmatrix}},$ wherein the sub-matrix on the diagonal line of R isrepresented as${{\underset{\underset{\_}{\_}}{R}}_{0} = {{\sum\limits_{i = 0}^{P - 1}{{\underset{\underset{\_}{\_}}{H}}_{i}{\underset{\underset{\_}{\_}}{H}}_{i}^{H}}} + \sigma_{v}^{2}}},$the rest sub-matrix thereof is represented as${{\underset{\underset{\_}{\_}}{R}}_{p} = {\sum\limits_{i = 0}^{P - p - 1}{{\underset{\underset{\_}{\_}}{H}}_{i}{\underset{\underset{\_}{\_}}{H}}_{i + p}^{H}}}},{p = 1},2,\ldots \mspace{14mu},{P - 1},$wherein the superscript H represents a Hermitian operation, and σ_(v) ²represents a variance of a Gaussian noise.
 18. The equalization methodaccording to claim 17, wherein the step of performing the MMSE algorithmto the gains corresponding to the delay paths of the P clusters toobtain the plurality of N^(th) weights w=(w ₁ ^(T) w ₂ ^(T) . . . Sw_(P)^(T))^(T) comprises: performing the channel estimation; composing Psteering vectors according to the channel response by the channelestimation estimated from the P channel estimation windows; performing adiscrete Fourier transform to the steering vectors, wherein the discreteFourier transform is performed to the p^(th) steering vector h _(p) toobtain F·h _(p) and generate F frequency components; generating theauto-correlation matrix R by utilizing the channel response from thechannel estimation; calculating circulant matrixes S ₀˜S _(P-1)respectively similar to the sub-matrixes R ₀˜R _(P-1) from theautocorrelation matrix R and extracting the elements [S ₀]₁˜[S _(P-1)]₁of the first column from the circulant matrixes S ₀˜S _(P-1); performing[S ₀]₁˜[S _(P-1)]₁ with the discrete Fourier transform to obtain thediagonal matrix D ₀˜D_(P-1), wherein the p^(th) diagonal matrix isrepresented as D _(p)=diag{F·[S _(p)]₁}; composing the matrix Daccording to the diagonal matrix D ₀˜D _(P-1); respectively generating Fparticular matrixes Λ ₁˜Λ _(F) according to the matrix D and calculatingthe inverse matrixes (Λ ₁)⁻¹˜(Λ _(F))⁻¹ from the particular matrixes,wherein the k^(th) particular matrix is represented as${{\underset{\underset{\_}{\_}}{\Lambda}}_{k} = \begin{pmatrix}{{\underset{\underset{\_}{\_}}{D}}_{0}\lbrack k\rbrack} & {{\underset{\underset{\_}{\_}}{D}}_{1}\lbrack k\rbrack}^{*} & \cdots & {{\underset{\underset{\_}{\_}}{D}}_{P - 1}\lbrack k\rbrack}^{*} \\{{\underset{\underset{\_}{\_}}{D}}_{1}\lbrack k\rbrack} & {{\underset{\underset{\_}{\_}}{D}}_{0}\lbrack k\rbrack} & \ddots & {{\underset{\underset{\_}{\_}}{D}}_{P - 2}\lbrack k\rbrack}^{*} \\\vdots & \ddots & \ddots & \vdots \\{{\underset{\underset{\_}{\_}}{D}}_{P - 1}\lbrack k\rbrack} & {{\underset{\underset{\_}{\_}}{D}}_{P - 2}\lbrack k\rbrack} & \cdots & {{\underset{\underset{\_}{\_}}{D}}_{0}\lbrack k\rbrack}\end{pmatrix}},$ wherein D _(p)[k] represents the k^(th) element of thediagonal matrix D _(p), where k=1, 2, . . . , F; performingde-correlation operation for F times, wherein i^(th) de-correlationoperation receives the i^(th) frequency component of the discreteFourier transform result F·h _(p) and correspondingly multiplies Pfrequency components to the elements of the P^(th) row from the matrix(Λ _(i))⁻¹ to output P pieces of sum of product, wherein i=1, 2, . . . ,F; and performing inverse Fourier transform for P times, wherein thej^(th) inverse Fourier transform receives the j^(th) sum of product, andperforms the inverse Fourier transform to received F pieces of sum ofproduct to output weight w _(j), wherein j=1, 2, . . . , P.